Resolving write conflicts in a dispersed storage network

ABSTRACT

A method begins by first and second client devices transmitting first and second sets of write requests to storage units. The method continues with a storage unit sending a write response message to the first and second client devices, where the write response message indicates a storage unit score value for one of the client devices. The method continues with the first and second client devices interpreting the storage unit score values from the storage units to determine which client device has write priority. The method continues with the client device that has the write priority sending a set of next-phase write requests to the storage units. The method continues with the other client device that does not have the write priority sending a set of rollback requests to the storage units.

CROSS REFERENCE TO RELATED PATENTS

The present U.S. Utility Patent Application claims priority pursuant to35 U.S.C. §119(e) to U.S. Provisional Application No. 61/769,595,entitled “SECURELY STORING DATA WITHOUT DUPLICATION IN A DISPERSEDSTORAGE NETWORK,” filed Feb. 26, 2013, which is hereby incorporatedherein by reference in its entirety and made part of the present U.S.Utility Patent Application for all purposes.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT-NOTAPPLICABLE INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACTDISC-NOT APPLICABLE BACKGROUND OF THE INVENTION

1. Technical Field of the Invention

This invention relates generally to computer networks and moreparticularly to dispersed storage of data and distributed taskprocessing of data.

2. Description of Related Art

Computing devices are known to communicate data, process data, and/orstore data. Such computing devices range from wireless smart phones,laptops, tablets, personal computers (PC), work stations, and video gamedevices, to data centers that support millions of web searches, stocktrades, or on-line purchases every day. In general, a computing deviceincludes a central processing unit (CPU), a memory system, userinput/output interfaces, peripheral device interfaces, and aninterconnecting bus structure.

As is further known, a computer may effectively extend its CPU by using“cloud computing” to perform one or more computing functions (e.g., aservice, an application, an algorithm, an arithmetic logic function,etc.) on behalf of the computer. Further, for large services,applications, and/or functions, cloud computing may be performed bymultiple cloud computing resources in a distributed manner to improvethe response time for completion of the service, application, and/orfunction. For example, Hadoop is an open source software framework thatsupports distributed applications enabling application execution bythousands of computers.

In addition to cloud computing, a computer may use “cloud storage” aspart of its memory system. As is known, cloud storage enables a user,via its computer, to store files, applications, etc. on an Internetstorage system. The Internet storage system may include a RAID(redundant array of independent disks) system and/or a dispersed storagesystem that uses an error correction scheme to encode data for storage.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a distributedcomputing system in accordance with the present invention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the present invention;

FIG. 3 is a diagram of an example of a distributed storage and taskprocessing in accordance with the present invention;

FIG. 4 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing in accordance with thepresent invention;

FIG. 5 is a logic diagram of an example of a method for outbound DSTprocessing in accordance with the present invention;

FIG. 6 is a schematic block diagram of an embodiment of a dispersederror encoding in accordance with the present invention;

FIG. 7 is a diagram of an example of a segment processing of thedispersed error encoding in accordance with the present invention;

FIG. 8 is a diagram of an example of error encoding and slicingprocessing of the dispersed error encoding in accordance with thepresent invention;

FIG. 9 is a diagram of an example of grouping selection processing ofthe outbound DST processing in accordance with the present invention;

FIG. 10 is a diagram of an example of converting data into slice groupsin accordance with the present invention;

FIG. 11 is a schematic block diagram of an embodiment of a DST executionunit in accordance with the present invention;

FIG. 12 is a schematic block diagram of an example of operation of a DSTexecution unit in accordance with the present invention;

FIG. 13 is a schematic block diagram of an embodiment of an inbounddistributed storage and/or task (DST) processing in accordance with thepresent invention;

FIG. 14 is a logic diagram of an example of a method for inbound DSTprocessing in accordance with the present invention;

FIG. 15 is a diagram of an example of de-grouping selection processingof the inbound DST processing in accordance with the present invention;

FIG. 16 is a schematic block diagram of an embodiment of a dispersederror decoding in accordance with the present invention;

FIG. 17 is a diagram of an example of de-slicing and error decodingprocessing of the dispersed error decoding in accordance with thepresent invention;

FIG. 18 is a diagram of an example of a de-segment processing of thedispersed error decoding in accordance with the present invention;

FIG. 19 is a diagram of an example of converting slice groups into datain accordance with the present invention;

FIG. 20 is a diagram of an example of a distributed storage within thedistributed computing system in accordance with the present invention;

FIG. 21 is a schematic block diagram of an example of operation ofoutbound distributed storage and/or task (DST) processing for storingdata in accordance with the present invention;

FIG. 22 is a schematic block diagram of an example of a dispersed errorencoding for the example of FIG. 21 in accordance with the presentinvention;

FIG. 23 is a diagram of an example of converting data into pillar slicegroups for storage in accordance with the present invention;

FIG. 24 is a schematic block diagram of an example of a storageoperation of a DST execution unit in accordance with the presentinvention;

FIG. 25 is a schematic block diagram of an example of operation ofinbound distributed storage and/or task (DST) processing for retrievingdispersed error encoded data in accordance with the present invention;

FIG. 26 is a schematic block diagram of an example of a dispersed errordecoding for the example of FIG. 25 in accordance with the presentinvention;

FIG. 27 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing a plurality ofdata and a plurality of task codes in accordance with the presentinvention;

FIG. 28 is a schematic block diagram of an example of the distributedcomputing system performing tasks on stored data in accordance with thepresent invention;

FIG. 29 is a schematic block diagram of an embodiment of a taskdistribution module facilitating the example of FIG. 28 in accordancewith the present invention;

FIG. 30 is a diagram of a specific example of the distributed computingsystem performing tasks on stored data in accordance with the presentinvention;

FIG. 31 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing data and taskcodes for the example of FIG. 30 in accordance with the presentinvention;

FIG. 32 is a diagram of an example of DST allocation information for theexample of FIG. 30 in accordance with the present invention;

FIGS. 33-38 are schematic block diagrams of the DSTN module performingthe example of FIG. 30 in accordance with the present invention;

FIG. 39 is a diagram of an example of combining result information intofinal results for the example of FIG. 30 in accordance with the presentinvention;

FIG. 40A is a schematic block diagram of an embodiment of a dispersedstorage system in accordance with the present invention;

FIG. 40B is a schematic block diagram of a user device in accordancewith the present invention;

FIG. 40C is a flowchart illustrating an example of accessingnon-redundant data in accordance with the present invention;

FIG. 41A is a schematic block diagram of a data encryption system inaccordance with the present invention;

FIG. 41B is a flowchart illustrating an example of securely storing datain accordance with the present invention;

FIG. 42A is a schematic block diagram of another distributed storage andtask (DST processing unit in accordance with the present invention;

FIG. 42B is a flowchart illustrating an example of assigning processingresources in accordance with the present invention;

FIG. 43A is a schematic block diagram of a dispersed storage networkmemory in accordance with the present invention;

FIG. 43B is a flowchart illustrating an example of rebuilding a slice tobe rebuilt in accordance with the present invention;

FIG. 44A is a schematic block diagram of another embodiment of adispersed storage system in accordance with the present invention;

FIG. 44B is a flowchart illustrating an example of replicating data inaccordance with the present invention;

FIG. 45A is a schematic block diagram of another embodiment of adispersed storage system in accordance with the present invention;

FIG. 45B is a flowchart illustrating an example of storing datautilizing a random writes in accordance with the present invention;

FIGS. 46A, D, and E are schematic block diagrams of an embodiment of adispersed storage network in accordance with the present invention;

FIG. 46B is a diagram illustrating an example of timing of a storageprocess in accordance with the present invention;

FIG. 46C is a table illustrating assigning storage unit score values inaccordance with the present invention;

FIG. 46F is a flowchart illustrating an example of resolving writeconflicts in accordance with the present invention;

FIG. 46G is a flowchart illustrating another example of resolving writeconflicts in accordance with the present invention;

FIG. 47A is a schematic block diagram of another embodiment of adispersed storage system in accordance with the present invention;

FIG. 47B is a flowchart illustrating an example of writing data inaccordance with the present invention; and

FIG. 47C is a flowchart illustrating an example of deleting partiallywritten data in accordance with the present invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of an embodiment of a distributedcomputing system 10 that includes a user device 12 and/or a user device14, a distributed storage and/or task (DST) processing unit 16, adistributed storage and/or task network (DSTN) managing unit 18, a DSTintegrity processing unit 20, and a distributed storage and/or tasknetwork (DSTN) module 22. The components of the distributed computingsystem 10 are coupled via a network 24, which may include one or morewireless and/or wire lined communication systems; one or more privateintranet systems and/or public internet systems; and/or one or morelocal area networks (LAN) and/or wide area networks (WAN).

The DSTN module 22 includes a plurality of distributed storage and/ortask (DST) execution units 36 that may be located at geographicallydifferent sites (e.g., one in Chicago, one in Milwaukee, etc.). Each ofthe DST execution units is operable to store dispersed error encodeddata and/or to execute, in a distributed manner, one or more tasks ondata. The tasks may be a simple function (e.g., a mathematical function,a logic function, an identify function, a find function, a search enginefunction, a replace function, etc.), a complex function (e.g.,compression, human and/or computer language translation, text-to-voiceconversion, voice-to-text conversion, etc.), multiple simple and/orcomplex functions, one or more algorithms, one or more applications,etc.

Each of the user devices 12-14, the DST processing unit 16, the DSTNmanaging unit 18, and the DST integrity processing unit 20 include acomputing core 26 and may be a portable computing device and/or a fixedcomputing device. A portable computing device may be a social networkingdevice, a gaming device, a cell phone, a smart phone, a personal digitalassistant, a digital music player, a digital video player, a laptopcomputer, a handheld computer, a tablet, a video game controller, and/orany other portable device that includes a computing core. A fixedcomputing device may be a personal computer (PC), a computer server, acable set-top box, a satellite receiver, a television set, a printer, afax machine, home entertainment equipment, a video game console, and/orany type of home or office computing equipment. User device 12 and DSTprocessing unit 16 are configured to include a DST client module 34.

With respect to interfaces, each interface 30, 32, and 33 includessoftware and/or hardware to support one or more communication links viathe network 24 indirectly and/or directly. For example, interface 30supports a communication link (e.g., wired, wireless, direct, via a LAN,via the network 24, etc.) between user device 14 and the DST processingunit 16. As another example, interface 32 supports communication links(e.g., a wired connection, a wireless connection, a LAN connection,and/or any other type of connection to/from the network 24) between userdevice 12 and the DSTN module 22 and between the DST processing unit 16and the DSTN module 22. As yet another example, interface 33 supports acommunication link for each of the DSTN managing unit 18 and DSTintegrity processing unit 20 to the network 24.

The distributed computing system 10 is operable to support dispersedstorage (DS) error encoded data storage and retrieval, to supportdistributed task processing on received data, and/or to supportdistributed task processing on stored data. In general and with respectto DS error encoded data storage and retrieval, the distributedcomputing system 10 supports three primary operations: storagemanagement, data storage and retrieval (an example of which will bediscussed with reference to FIGS. 20-26), and data storage integrityverification. In accordance with these three primary functions, data canbe encoded, distributedly stored in physically different locations, andsubsequently retrieved in a reliable and secure manner. Such a system istolerant of a significant number of failures (e.g., up to a failurelevel, which may be greater than or equal to a pillar width minus adecode threshold minus one) that may result from individual storagedevice failures and/or network equipment failures without loss of dataand without the need for a redundant or backup copy. Further, the systemallows the data to be stored for an indefinite period of time withoutdata loss and does so in a secure manner (e.g., the system is veryresistant to attempts at hacking the data).

The second primary function (i.e., distributed data storage andretrieval) begins and ends with a user device 12-14. For instance, if asecond type of user device 14 has data 40 to store in the DSTN module22, it sends the data 40 to the DST processing unit 16 via its interface30. The interface 30 functions to mimic a conventional operating system(OS) file system interface (e.g., network file system (NFS), flash filesystem (FFS), disk file system (DFS), file transfer protocol (FTP),web-based distributed authoring and versioning (WebDAV), etc.) and/or ablock memory interface (e.g., small computer system interface (SCSI),internet small computer system interface (iSCSI), etc.). In addition,the interface 30 may attach a user identification code (ID) to the data40.

To support storage management, the DSTN managing unit 18 performs DSmanagement services. One such DS management service includes the DSTNmanaging unit 18 establishing distributed data storage parameters (e.g.,vault creation, distributed storage parameters, security parameters,billing information, user profile information, etc.) for a user device12-14 individually or as part of a group of user devices. For example,the DSTN managing unit 18 coordinates creation of a vault (e.g., avirtual memory block) within memory of the DSTN module 22 for a userdevice, a group of devices, or for public access and establishes pervault dispersed storage (DS) error encoding parameters for a vault. TheDSTN managing unit 18 may facilitate storage of DS error encodingparameters for each vault of a plurality of vaults by updating registryinformation for the distributed computing system 10. The facilitatingincludes storing updated registry information in one or more of the DSTNmodule 22, the user device 12, the DST processing unit 16, and the DSTintegrity processing unit 20.

The DS error encoding parameters (e.g. or dispersed storage error codingparameters) include data segmenting information (e.g., how many segmentsdata (e.g., a file, a group of files, a data block, etc.) is dividedinto), segment security information (e.g., per segment encryption,compression, integrity checksum, etc.), error coding information (e.g.,pillar width, decode threshold, read threshold, write threshold, etc.),slicing information (e.g., the number of encoded data slices that willbe created for each data segment); and slice security information (e.g.,per encoded data slice encryption, compression, integrity checksum,etc.).

The DSTN managing unit 18 creates and stores user profile information(e.g., an access control list (ACL)) in local memory and/or withinmemory of the DSTN module 22. The user profile information includesauthentication information, permissions, and/or the security parameters.The security parameters may include encryption/decryption scheme, one ormore encryption keys, key generation scheme, and/or dataencoding/decoding scheme.

The DSTN managing unit 18 creates billing information for a particularuser, a user group, a vault access, public vault access, etc. Forinstance, the DSTN managing unit 18 tracks the number of times a useraccesses a private vault and/or public vaults, which can be used togenerate a per-access billing information. In another instance, the DSTNmanaging unit 18 tracks the amount of data stored and/or retrieved by auser device and/or a user group, which can be used to generate aper-data-amount billing information.

Another DS management service includes the DSTN managing unit 18performing network operations, network administration, and/or networkmaintenance. Network operations includes authenticating user dataallocation requests (e.g., read and/or write requests), managingcreation of vaults, establishing authentication credentials for userdevices, adding/deleting components (e.g., user devices, DST executionunits, and/or DST processing units) from the distributed computingsystem 10, and/or establishing authentication credentials for DSTexecution units 36. Network administration includes monitoring devicesand/or units for failures, maintaining vault information, determiningdevice and/or unit activation status, determining device and/or unitloading, and/or determining any other system level operation thataffects the performance level of the system 10. Network maintenanceincludes facilitating replacing, upgrading, repairing, and/or expandinga device and/or unit of the system 10.

To support data storage integrity verification within the distributedcomputing system 10, the DST integrity processing unit 20 performsrebuilding of ‘bad’ or missing encoded data slices. At a high level, theDST integrity processing unit 20 performs rebuilding by periodicallyattempting to retrieve/list encoded data slices, and/or slice names ofthe encoded data slices, from the DSTN module 22. For retrieved encodedslices, they are checked for errors due to data corruption, outdatedversion, etc. If a slice includes an error, it is flagged as a ‘bad’slice. For encoded data slices that were not received and/or not listed,they are flagged as missing slices. Bad and/or missing slices aresubsequently rebuilt using other retrieved encoded data slices that aredeemed to be good slices to produce rebuilt slices. The rebuilt slicesare stored in memory of the DSTN module 22. Note that the DST integrityprocessing unit 20 may be a separate unit as shown, it may be includedin the DSTN module 22, it may be included in the DST processing unit 16,and/or distributed among the DST execution units 36.

To support distributed task processing on received data, the distributedcomputing system 10 has two primary operations: DST (distributed storageand/or task processing) management and DST execution on received data(an example of which will be discussed with reference to FIGS. 3-19).With respect to the storage portion of the DST management, the DSTNmanaging unit 18 functions as previously described. With respect to thetasking processing of the DST management, the DSTN managing unit 18performs distributed task processing (DTP) management services. One suchDTP management service includes the DSTN managing unit 18 establishingDTP parameters (e.g., user-vault affiliation information, billinginformation, user-task information, etc.) for a user device 12-14individually or as part of a group of user devices.

Another DTP management service includes the DSTN managing unit 18performing DTP network operations, network administration (which isessentially the same as described above), and/or network maintenance(which is essentially the same as described above). Network operationsinclude, but are not limited to, authenticating user task processingrequests (e.g., valid request, valid user, etc.), authenticating resultsand/or partial results, establishing DTP authentication credentials foruser devices, adding/deleting components (e.g., user devices, DSTexecution units, and/or DST processing units) from the distributedcomputing system, and/or establishing DTP authentication credentials forDST execution units.

To support distributed task processing on stored data, the distributedcomputing system 10 has two primary operations: DST (distributed storageand/or task) management and DST execution on stored data. With respectto the DST execution on stored data, if the second type of user device14 has a task request 38 for execution by the DSTN module 22, it sendsthe task request 38 to the DST processing unit 16 via its interface 30.An example of DST execution on stored data will be discussed in greaterdetail with reference to FIGS. 27-39. With respect to the DSTmanagement, it is substantially similar to the DST management to supportdistributed task processing on received data.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (IO)controller 56, a peripheral component interconnect (PCI) interface 58,an IO interface module 60, at least one IO device interface module 62, aread only memory (ROM) basic input output system (BIOS) 64, and one ormore memory interface modules. The one or more memory interfacemodule(s) includes one or more of a universal serial bus (USB) interfacemodule 66, a host bus adapter (HBA) interface module 68, a networkinterface module 70, a flash interface module 72, a hard drive interfacemodule 74, and a DSTN interface module 76.

The DSTN interface module 76 functions to mimic a conventional operatingsystem (OS) file system interface (e.g., network file system (NFS),flash file system (FFS), disk file system (DFS), file transfer protocol(FTP), web-based distributed authoring and versioning (WebDAV), etc.)and/or a block memory interface (e.g., small computer system interface(SCSI), internet small computer system interface (iSCSI), etc.). TheDSTN interface module 76 and/or the network interface module 70 mayfunction as the interface 30 of the user device 14 of FIG. 1. Furthernote that the IO device interface module 62 and/or the memory interfacemodules may be collectively or individually referred to as IO ports.

FIG. 3 is a diagram of an example of the distributed computing systemperforming a distributed storage and task processing operation. Thedistributed computing system includes a DST (distributed storage and/ortask) client module 34 (which may be in user device 14 and/or in DSTprocessing unit 16 of FIG. 1), a network 24, a plurality of DSTexecution units 1-n that includes two or more DST execution units 36 ofFIG. 1 (which form at least a portion of DSTN module 22 of FIG. 1), aDST managing module (not shown), and a DST integrity verification module(not shown). The DST client module 34 includes an outbound DSTprocessing section 80 and an inbound DST processing section 82. Each ofthe DST execution units 1-n includes a controller 86, a processingmodule 84, memory 88, a DT (distributed task) execution module 90, and aDST client module 34.

In an example of operation, the DST client module 34 receives data 92and one or more tasks 94 to be performed upon the data 92. The data 92may be of any size and of any content, where, due to the size (e.g.,greater than a few Terra-Bytes), the content (e.g., secure data, etc.),and/or task(s) (e.g., MIPS intensive), distributed processing of thetask(s) on the data is desired. For example, the data 92 may be one ormore digital books, a copy of a company's emails, a large-scale Internetsearch, a video security file, one or more entertainment video files(e.g., television programs, movies, etc.), data files, and/or any otherlarge amount of data (e.g., greater than a few Terra-Bytes).

Within the DST client module 34, the outbound DST processing section 80receives the data 92 and the task(s) 94. The outbound DST processingsection 80 processes the data 92 to produce slice groupings 96. As anexample of such processing, the outbound DST processing section 80partitions the data 92 into a plurality of data partitions. For eachdata partition, the outbound DST processing section 80 dispersed storage(DS) error encodes the data partition to produce encoded data slices andgroups the encoded data slices into a slice grouping 96. In addition,the outbound DST processing section 80 partitions the task 94 intopartial tasks 98, where the number of partial tasks 98 may correspond tothe number of slice groupings 96.

The outbound DST processing section 80 then sends, via the network 24,the slice groupings 96 and the partial tasks 98 to the DST executionunits 1-n of the DSTN module 22 of FIG. 1. For example, the outbound DSTprocessing section 80 sends slice group 1 and partial task 1 to DSTexecution unit 1. As another example, the outbound DST processingsection 80 sends slice group #n and partial task #n to DST executionunit #n.

Each DST execution unit performs its partial task 98 upon its slicegroup 96 to produce partial results 102. For example, DST execution unit#1 performs partial task #1 on slice group #1 to produce a partialresult #1, for results. As a more specific example, slice group #1corresponds to a data partition of a series of digital books and thepartial task #1 corresponds to searching for specific phrases, recordingwhere the phrase is found, and establishing a phrase count. In this morespecific example, the partial result #1 includes information as to wherethe phrase was found and includes the phrase count.

Upon completion of generating their respective partial results 102, theDST execution units send, via the network 24, their partial results 102to the inbound DST processing section 82 of the DST client module 34.The inbound DST processing section 82 processes the received partialresults 102 to produce a result 104. Continuing with the specificexample of the preceding paragraph, the inbound DST processing section82 combines the phrase count from each of the DST execution units 36 toproduce a total phrase count. In addition, the inbound DST processingsection 82 combines the ‘where the phrase was found’ information fromeach of the DST execution units 36 within their respective datapartitions to produce ‘where the phrase was found’ information for theseries of digital books.

In another example of operation, the DST client module 34 requestsretrieval of stored data within the memory of the DST execution units 36(e.g., memory of the DSTN module). In this example, the task 94 isretrieve data stored in the memory of the DSTN module. Accordingly, theoutbound DST processing section 80 converts the task 94 into a pluralityof partial tasks 98 and sends the partial tasks 98 to the respective DSTexecution units 1-n.

In response to the partial task 98 of retrieving stored data, a DSTexecution unit 36 identifies the corresponding encoded data slices 100and retrieves them. For example, DST execution unit #1 receives partialtask #1 and retrieves, in response thereto, retrieved slices #1. The DSTexecution units 36 send their respective retrieved slices 100 to theinbound DST processing section 82 via the network 24.

The inbound DST processing section 82 converts the retrieved slices 100into data 92. For example, the inbound DST processing section 82de-groups the retrieved slices 100 to produce encoded slices per datapartition. The inbound DST processing section 82 then DS error decodesthe encoded slices per data partition to produce data partitions. Theinbound DST processing section 82 de-partitions the data partitions torecapture the data 92.

FIG. 4 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing section 80 of a DSTclient module 34 FIG. 1 coupled to a DSTN module 22 of a FIG. 1 (e.g., aplurality of n DST execution units 36) via a network 24. The outboundDST processing section 80 includes a data partitioning module 110, adispersed storage (DS) error encoding module 112, a grouping selectormodule 114, a control module 116, and a distributed task control module118.

In an example of operation, the data partitioning module 110 partitionsdata 92 into a plurality of data partitions 120. The number ofpartitions and the size of the partitions may be selected by the controlmodule 116 via control 160 based on the data 92 (e.g., its size, itscontent, etc.), a corresponding task 94 to be performed (e.g., simple,complex, single step, multiple steps, etc.), DS encoding parameters(e.g., pillar width, decode threshold, write threshold, segment securityparameters, slice security parameters, etc.), capabilities of the DSTexecution units 36 (e.g., processing resources, availability ofprocessing recourses, etc.), and/or as may be inputted by a user, systemadministrator, or other operator (human or automated). For example, thedata partitioning module 110 partitions the data 92 (e.g., 100Terra-Bytes) into 100,000 data segments, each being 1 Giga-Byte in size.Alternatively, the data partitioning module 110 partitions the data 92into a plurality of data segments, where some of data segments are of adifferent size, are of the same size, or a combination thereof.

The DS error encoding module 112 receives the data partitions 120 in aserial manner, a parallel manner, and/or a combination thereof. For eachdata partition 120, the DS error encoding module 112 DS error encodesthe data partition 120 in accordance with control information 160 fromthe control module 116 to produce encoded data slices 122. The DS errorencoding includes segmenting the data partition into data segments,segment security processing (e.g., encryption, compression,watermarking, integrity check (e.g., CRC), etc.), error encoding,slicing, and/or per slice security processing (e.g., encryption,compression, watermarking, integrity check (e.g., CRC), etc.). Thecontrol information 160 indicates which steps of the DS error encodingare active for a given data partition and, for active steps, indicatesthe parameters for the step. For example, the control information 160indicates that the error encoding is active and includes error encodingparameters (e.g., pillar width, decode threshold, write threshold, readthreshold, type of error encoding, etc.).

The grouping selector module 114 groups the encoded slices 122 of a datapartition into a set of slice groupings 96. The number of slicegroupings corresponds to the number of DST execution units 36 identifiedfor a particular task 94. For example, if five DST execution units 36are identified for the particular task 94, the grouping selector modulegroups the encoded slices 122 of a data partition into five slicegroupings 96. The grouping selector module 114 outputs the slicegroupings 96 to the corresponding DST execution units 36 via the network24.

The distributed task control module 118 receives the task 94 andconverts the task 94 into a set of partial tasks 98. For example, thedistributed task control module 118 receives a task to find where in thedata (e.g., a series of books) a phrase occurs and a total count of thephrase usage in the data. In this example, the distributed task controlmodule 118 replicates the task 94 for each DST execution unit 36 toproduce the partial tasks 98. In another example, the distributed taskcontrol module 118 receives a task to find where in the data a firstphrase occurs, where in the data a second phrase occurs, and a totalcount for each phrase usage in the data. In this example, thedistributed task control module 118 generates a first set of partialtasks 98 for finding and counting the first phase and a second set ofpartial tasks for finding and counting the second phrase. Thedistributed task control module 118 sends respective first and/or secondpartial tasks 98 to each DST execution unit 36.

FIG. 5 is a logic diagram of an example of a method for outbounddistributed storage and task (DST) processing that begins at step 126where a DST client module receives data and one or more correspondingtasks. The method continues at step 128 where the DST client moduledetermines a number of DST units to support the task for one or moredata partitions. For example, the DST client module may determine thenumber of DST units to support the task based on the size of the data,the requested task, the content of the data, a predetermined number(e.g., user indicated, system administrator determined, etc.), availableDST units, capability of the DST units, and/or any other factorregarding distributed task processing of the data. The DST client modulemay select the same DST units for each data partition, may selectdifferent DST units for the data partitions, or a combination thereof.

The method continues at step 130 where the DST client module determinesprocessing parameters of the data based on the number of DST unitsselected for distributed task processing. The processing parametersinclude data partitioning information, DS encoding parameters, and/orslice grouping information. The data partitioning information includes anumber of data partitions, size of each data partition, and/ororganization of the data partitions (e.g., number of data blocks in apartition, the size of the data blocks, and arrangement of the datablocks). The DS encoding parameters include segmenting information,segment security information, error encoding information (e.g.,dispersed storage error encoding function parameters including one ormore of pillar width, decode threshold, write threshold, read threshold,generator matrix), slicing information, and/or per slice securityinformation. The slice grouping information includes informationregarding how to arrange the encoded data slices into groups for theselected DST units. As a specific example, if the DST client moduledetermines that five DST units are needed to support the task, then itdetermines that the error encoding parameters include a pillar width offive and a decode threshold of three.

The method continues at step 132 where the DST client module determinestask partitioning information (e.g., how to partition the tasks) basedon the selected DST units and data processing parameters. The dataprocessing parameters include the processing parameters and DST unitcapability information. The DST unit capability information includes thenumber of DT (distributed task) execution units, execution capabilitiesof each DT execution unit (e.g., MIPS capabilities, processing resources(e.g., quantity and capability of microprocessors, CPUs, digital signalprocessors, co-processor, microcontrollers, arithmetic logic circuitry,and/or and the other analog and/or digital processing circuitry),availability of the processing resources, memory information (e.g.,type, size, availability, etc.)), and/or any information germane toexecuting one or more tasks.

The method continues at step 134 where the DST client module processesthe data in accordance with the processing parameters to produce slicegroupings. The method continues at step 136 where the DST client modulepartitions the task based on the task partitioning information toproduce a set of partial tasks. The method continues at step 138 wherethe DST client module sends the slice groupings and the correspondingpartial tasks to respective DST units.

FIG. 6 is a schematic block diagram of an embodiment of the dispersedstorage (DS) error encoding module 112 of an outbound distributedstorage and task (DST) processing section. The DS error encoding module112 includes a segment processing module 142, a segment securityprocessing module 144, an error encoding module 146, a slicing module148, and a per slice security processing module 150. Each of thesemodules is coupled to a control module 116 to receive controlinformation 160 therefrom.

In an example of operation, the segment processing module 142 receives adata partition 120 from a data partitioning module and receivessegmenting information as the control information 160 from the controlmodule 116. The segmenting information indicates how the segmentprocessing module 142 is to segment the data partition 120. For example,the segmenting information indicates how many rows to segment the databased on a decode threshold of an error encoding scheme, indicates howmany columns to segment the data into based on a number and size of datablocks within the data partition 120, and indicates how many columns toinclude in a data segment 152. The segment processing module 142segments the data 120 into data segments 152 in accordance with thesegmenting information.

The segment security processing module 144, when enabled by the controlmodule 116, secures the data segments 152 based on segment securityinformation received as control information 160 from the control module116. The segment security information includes data compression,encryption, watermarking, integrity check (e.g., cyclic redundancy check(CRC), etc.), and/or any other type of digital security. For example,when the segment security processing module 144 is enabled, it maycompress a data segment 152, encrypt the compressed data segment, andgenerate a CRC value for the encrypted data segment to produce a securedata segment 154. When the segment security processing module 144 is notenabled, it passes the data segments 152 to the error encoding module146 or is bypassed such that the data segments 152 are provided to theerror encoding module 146.

The error encoding module 146 encodes the secure data segments 154 inaccordance with error correction encoding parameters received as controlinformation 160 from the control module 116. The error correctionencoding parameters (e.g., also referred to as dispersed storage errorcoding parameters) include identifying an error correction encodingscheme (e.g., forward error correction algorithm, a Reed-Solomon basedalgorithm, an online coding algorithm, an information dispersalalgorithm, etc.), a pillar width, a decode threshold, a read threshold,a write threshold, etc. For example, the error correction encodingparameters identify a specific error correction encoding scheme,specifies a pillar width of five, and specifies a decode threshold ofthree. From these parameters, the error encoding module 146 encodes adata segment 154 to produce an encoded data segment 156.

The slicing module 148 slices the encoded data segment 156 in accordancewith the pillar width of the error correction encoding parametersreceived as control information 160. For example, if the pillar width isfive, the slicing module 148 slices an encoded data segment 156 into aset of five encoded data slices. As such, for a plurality of encodeddata segments 156 for a given data partition, the slicing module outputsa plurality of sets of encoded data slices 158.

The per slice security processing module 150, when enabled by thecontrol module 116, secures each encoded data slice 158 based on slicesecurity information received as control information 160 from thecontrol module 116. The slice security information includes datacompression, encryption, watermarking, integrity check (e.g., CRC,etc.), and/or any other type of digital security. For example, when theper slice security processing module 150 is enabled, it compresses anencoded data slice 158, encrypts the compressed encoded data slice, andgenerates a CRC value for the encrypted encoded data slice to produce asecure encoded data slice 122. When the per slice security processingmodule 150 is not enabled, it passes the encoded data slices 158 or isbypassed such that the encoded data slices 158 are the output of the DSerror encoding module 112. Note that the control module 116 may beomitted and each module stores its own parameters.

FIG. 7 is a diagram of an example of a segment processing of a dispersedstorage (DS) error encoding module. In this example, a segmentprocessing module 142 receives a data partition 120 that includes 45data blocks (e.g., d1-d45), receives segmenting information (i.e.,control information 160) from a control module, and segments the datapartition 120 in accordance with the control information 160 to producedata segments 152. Each data block may be of the same size as other datablocks or of a different size. In addition, the size of each data blockmay be a few bytes to megabytes of data. As previously mentioned, thesegmenting information indicates how many rows to segment the datapartition into, indicates how many columns to segment the data partitioninto, and indicates how many columns to include in a data segment.

In this example, the decode threshold of the error encoding scheme isthree; as such the number of rows to divide the data partition into isthree. The number of columns for each row is set to 15, which is basedon the number and size of data blocks. The data blocks of the datapartition are arranged in rows and columns in a sequential order (i.e.,the first row includes the first 15 data blocks; the second row includesthe second 15 data blocks; and the third row includes the last 15 datablocks).

With the data blocks arranged into the desired sequential order, theyare divided into data segments based on the segmenting information. Inthis example, the data partition is divided into 8 data segments; thefirst 7 include 2 columns of three rows and the last includes 1 columnof three rows. Note that the first row of the 8 data segments is insequential order of the first 15 data blocks; the second row of the 8data segments in sequential order of the second 15 data blocks; and thethird row of the 8 data segments in sequential order of the last 15 datablocks. Note that the number of data blocks, the grouping of the datablocks into segments, and size of the data blocks may vary toaccommodate the desired distributed task processing function.

FIG. 8 is a diagram of an example of error encoding and slicingprocessing of the dispersed error encoding processing the data segmentsof FIG. 7. In this example, data segment 1 includes 3 rows with each rowbeing treated as one word for encoding. As such, data segment 1 includesthree words for encoding: word 1 including data blocks d1 and d2, word 2including data blocks d16 and d17, and word 3 including data blocks d31and d32. Each of data segments 2-7 includes three words where each wordincludes two data blocks. Data segment 8 includes three words where eachword includes a single data block (e.g., d15, d30, and d45).

In operation, an error encoding module 146 and a slicing module 148convert each data segment into a set of encoded data slices inaccordance with error correction encoding parameters as controlinformation 160. More specifically, when the error correction encodingparameters indicate a unity matrix Reed-Solomon based encodingalgorithm, 5 pillars, and decode threshold of 3, the first three encodeddata slices of the set of encoded data slices for a data segment aresubstantially similar to the corresponding word of the data segment. Forinstance, when the unity matrix Reed-Solomon based encoding algorithm isapplied to data segment 1, the content of the first encoded data slice(DS1_d1&2) of the first set of encoded data slices (e.g., correspondingto data segment 1) is substantially similar to content of the first word(e.g., d1 & d2); the content of the second encoded data slice(DS1_d16&17) of the first set of encoded data slices is substantiallysimilar to content of the second word (e.g., d16 & d17); and the contentof the third encoded data slice (DS1_d31&32) of the first set of encodeddata slices is substantially similar to content of the third word (e.g.,d31 & d32).

The content of the fourth and fifth encoded data slices (e.g., ES1_1 andES1_2) of the first set of encoded data slices include error correctiondata based on the first-third words of the first data segment. With suchan encoding and slicing scheme, retrieving any three of the five encodeddata slices allows the data segment to be accurately reconstructed.

The encoding and slicing of data segments 2-7 yield sets of encoded dataslices similar to the set of encoded data slices of data segment 1. Forinstance, the content of the first encoded data slice (DS2_d3&4) of thesecond set of encoded data slices (e.g., corresponding to data segment2) is substantially similar to content of the first word (e.g., d3 &d4); the content of the second encoded data slice (DS2_d18&19) of thesecond set of encoded data slices is substantially similar to content ofthe second word (e.g., d18 & d19); and the content of the third encodeddata slice (DS2_d33&34) of the second set of encoded data slices issubstantially similar to content of the third word (e.g., d33 & d34).The content of the fourth and fifth encoded data slices (e.g., ES1_1 andES1_2) of the second set of encoded data slices includes errorcorrection data based on the first-third words of the second datasegment.

FIG. 9 is a diagram of an example of grouping selection processing of anoutbound distributed storage and task (DST) processing in accordancewith group selection information as control information 160 from acontrol module. Encoded slices for data partition 122 are grouped inaccordance with the control information 160 to produce slice groupings96. In this example, a grouping selector module 114 organizes theencoded data slices into five slice groupings (e.g., one for each DSTexecution unit of a distributed storage and task network (DSTN) module).As a specific example, the grouping selector module 114 creates a firstslice grouping for a DST execution unit #1, which includes first encodedslices of each of the sets of encoded slices. As such, the first DSTexecution unit receives encoded data slices corresponding to data blocks1-15 (e.g., encoded data slices of contiguous data).

The grouping selection module 114 also creates a second slice groupingfor a DST execution unit #2, which includes second encoded slices ofeach of the sets of encoded slices. As such, the second DST executionunit receives encoded data slices corresponding to data blocks 16-30.The grouping selection module 114 further creates a third slice groupingfor DST execution unit #3, which includes third encoded slices of eachof the sets of encoded slices. As such, the third DST execution unitreceives encoded data slices corresponding to data blocks 31-45.

The grouping selection module 114 creates a fourth slice grouping forDST execution unit #4, which includes fourth encoded slices of each ofthe sets of encoded slices. As such, the fourth DST execution unitreceives encoded data slices corresponding to first error encodinginformation (e.g., encoded data slices of error coding (EC) data). Thegrouping selection module 114 further creates a fifth slice grouping forDST execution unit #5, which includes fifth encoded slices of each ofthe sets of encoded slices. As such, the fifth DST execution unitreceives encoded data slices corresponding to second error encodinginformation.

FIG. 10 is a diagram of an example of converting data 92 into slicegroups that expands on the preceding figures. As shown, the data 92 ispartitioned in accordance with a partitioning function 164 into aplurality of data partitions (1-x, where x is an integer greater than4). Each data partition (or chunkset of data) is encoded and groupedinto slice groupings as previously discussed by an encoding and groupingfunction 166. For a given data partition, the slice groupings are sentto distributed storage and task (DST) execution units. From datapartition to data partition, the ordering of the slice groupings to theDST execution units may vary.

For example, the slice groupings of data partition #1 is sent to the DSTexecution units such that the first DST execution receives first encodeddata slices of each of the sets of encoded data slices, whichcorresponds to a first continuous data chunk of the first data partition(e.g., refer to FIG. 9), a second DST execution receives second encodeddata slices of each of the sets of encoded data slices, whichcorresponds to a second continuous data chunk of the first datapartition, etc.

For the second data partition, the slice groupings may be sent to theDST execution units in a different order than it was done for the firstdata partition. For instance, the first slice grouping of the seconddata partition (e.g., slice group 2_1) is sent to the second DSTexecution unit; the second slice grouping of the second data partition(e.g., slice group 2_2) is sent to the third DST execution unit; thethird slice grouping of the second data partition (e.g., slice group2_3) is sent to the fourth DST execution unit; the fourth slice groupingof the second data partition (e.g., slice group 2_4, which includesfirst error coding information) is sent to the fifth DST execution unit;and the fifth slice grouping of the second data partition (e.g., slicegroup 2_5, which includes second error coding information) is sent tothe first DST execution unit.

The pattern of sending the slice groupings to the set of DST executionunits may vary in a predicted pattern, a random pattern, and/or acombination thereof from data partition to data partition. In addition,from data partition to data partition, the set of DST execution unitsmay change. For example, for the first data partition, DST executionunits 1-5 may be used; for the second data partition, DST executionunits 6-10 may be used; for the third data partition, DST executionunits 3-7 may be used; etc. As is also shown, the task is divided intopartial tasks that are sent to the DST execution units in conjunctionwith the slice groupings of the data partitions.

FIG. 11 is a schematic block diagram of an embodiment of a DST(distributed storage and/or task) execution unit that includes aninterface 169, a controller 86, memory 88, one or more DT (distributedtask) execution modules 90, and a DST client module 34. The memory 88 isof sufficient size to store a significant number of encoded data slices(e.g., thousands of slices to hundreds-of-millions of slices) and mayinclude one or more hard drives and/or one or more solid-state memorydevices (e.g., flash memory, DRAM, etc.).

In an example of storing a slice group, the DST execution modulereceives a slice grouping 96 (e.g., slice group #1) via interface 169.The slice grouping 96 includes, per partition, encoded data slices ofcontiguous data or encoded data slices of error coding (EC) data. Forslice group #1, the DST execution module receives encoded data slices ofcontiguous data for partitions #1 and #x (and potentially others between3 and x) and receives encoded data slices of EC data for partitions #2and #3 (and potentially others between 3 and x). Examples of encodeddata slices of contiguous data and encoded data slices of error coding(EC) data are discussed with reference to FIG. 9. The memory 88 storesthe encoded data slices of slice groupings 96 in accordance with memorycontrol information 174 it receives from the controller 86.

The controller 86 (e.g., a processing module, a CPU, etc.) generates thememory control information 174 based on a partial task(s) 98 anddistributed computing information (e.g., user information (e.g., userID, distributed computing permissions, data access permission, etc.),vault information (e.g., virtual memory assigned to user, user group,temporary storage for task processing, etc.), task validationinformation, etc.). For example, the controller 86 interprets thepartial task(s) 98 in light of the distributed computing information todetermine whether a requestor is authorized to perform the task 98, isauthorized to access the data, and/or is authorized to perform the taskon this particular data. When the requestor is authorized, thecontroller 86 determines, based on the task 98 and/or another input,whether the encoded data slices of the slice grouping 96 are to betemporarily stored or permanently stored. Based on the foregoing, thecontroller 86 generates the memory control information 174 to write theencoded data slices of the slice grouping 96 into the memory 88 and toindicate whether the slice grouping 96 is permanently stored ortemporarily stored.

With the slice grouping 96 stored in the memory 88, the controller 86facilitates execution of the partial task(s) 98. In an example, thecontroller 86 interprets the partial task 98 in light of thecapabilities of the DT execution module(s) 90. The capabilities includeone or more of MIPS capabilities, processing resources (e.g., quantityand capability of microprocessors, CPUs, digital signal processors,co-processor, microcontrollers, arithmetic logic circuitry, and/or anyother analog and/or digital processing circuitry), availability of theprocessing resources, etc. If the controller 86 determines that the DTexecution module(s) 90 have sufficient capabilities, it generates taskcontrol information 176.

The task control information 176 may be a generic instruction (e.g.,perform the task on the stored slice grouping) or a series ofoperational codes. In the former instance, the DT execution module 90includes a co-processor function specifically configured (fixed orprogrammed) to perform the desired task 98. In the latter instance, theDT execution module 90 includes a general processor topology where thecontroller stores an algorithm corresponding to the particular task 98.In this instance, the controller 86 provides the operational codes(e.g., assembly language, source code of a programming language, objectcode, etc.) of the algorithm to the DT execution module 90 forexecution.

Depending on the nature of the task 98, the DT execution module 90 maygenerate intermediate partial results 102 that are stored in the memory88 or in a cache memory (not shown) within the DT execution module 90.In either case, when the DT execution module 90 completes execution ofthe partial task 98, it outputs one or more partial results 102. Thepartial results 102 may also be stored in memory 88.

If, when the controller 86 is interpreting whether capabilities of theDT execution module(s) 90 can support the partial task 98, thecontroller 86 determines that the DT execution module(s) 90 cannotadequately support the task 98 (e.g., does not have the right resources,does not have sufficient available resources, available resources wouldbe too slow, etc.), it then determines whether the partial task 98should be fully offloaded or partially offloaded.

If the controller 86 determines that the partial task 98 should be fullyoffloaded, it generates DST control information 178 and provides it tothe DST client module 34. The DST control information 178 includes thepartial task 98, memory storage information regarding the slice grouping96, and distribution instructions. The distribution instructionsinstruct the DST client module 34 to divide the partial task 98 intosub-partial tasks 172, to divide the slice grouping 96 into sub-slicegroupings 170, and identify other DST execution units. The DST clientmodule 34 functions in a similar manner as the DST client module 34 ofFIGS. 3-10 to produce the sub-partial tasks 172 and the sub-slicegroupings 170 in accordance with the distribution instructions.

The DST client module 34 receives DST feedback 168 (e.g., sub-partialresults), via the interface 169, from the DST execution units to whichthe task was offloaded. The DST client module 34 provides thesub-partial results to the DST execution unit, which processes thesub-partial results to produce the partial result(s) 102.

If the controller 86 determines that the partial task 98 should bepartially offloaded, it determines what portion of the task 98 and/orslice grouping 96 should be processed locally and what should beoffloaded. For the portion that is being locally processed, thecontroller 86 generates task control information 176 as previouslydiscussed. For the portion that is being offloaded, the controller 86generates DST control information 178 as previously discussed.

When the DST client module 34 receives DST feedback 168 (e.g.,sub-partial results) from the DST executions units to which a portion ofthe task was offloaded, it provides the sub-partial results to the DTexecution module 90. The DT execution module 90 processes thesub-partial results with the sub-partial results it created to producethe partial result(s) 102.

The memory 88 may be further utilized to retrieve one or more of storedslices 100, stored results 104, partial results 102 when the DTexecution module 90 stores partial results 102 and/or results 104 in thememory 88. For example, when the partial task 98 includes a retrievalrequest, the controller 86 outputs the memory control 174 to the memory88 to facilitate retrieval of slices 100 and/or results 104.

FIG. 12 is a schematic block diagram of an example of operation of adistributed storage and task (DST) execution unit storing encoded dataslices and executing a task thereon. To store the encoded data slices ofa partition 1 of slice grouping 1, a controller 86 generates writecommands as memory control information 174 such that the encoded slicesare stored in desired locations (e.g., permanent or temporary) withinmemory 88.

Once the encoded slices are stored, the controller 86 provides taskcontrol information 176 to a distributed task (DT) execution module 90.As a first step of executing the task in accordance with the taskcontrol information 176, the DT execution module 90 retrieves theencoded slices from memory 88. The DT execution module 90 thenreconstructs contiguous data blocks of a data partition. As shown forthis example, reconstructed contiguous data blocks of data partition 1include data blocks 1-15 (e.g., d1-d15).

With the contiguous data blocks reconstructed, the DT execution module90 performs the task on the reconstructed contiguous data blocks. Forexample, the task may be to search the reconstructed contiguous datablocks for a particular word or phrase, identify where in thereconstructed contiguous data blocks the particular word or phraseoccurred, and/or count the occurrences of the particular word or phraseon the reconstructed contiguous data blocks. The DST execution unitcontinues in a similar manner for the encoded data slices of otherpartitions in slice grouping 1. Note that with using the unity matrixerror encoding scheme previously discussed, if the encoded data slicesof contiguous data are uncorrupted, the decoding of them is a relativelystraightforward process of extracting the data.

If, however, an encoded data slice of contiguous data is corrupted (ormissing), it can be rebuilt by accessing other DST execution units thatare storing the other encoded data slices of the set of encoded dataslices of the corrupted encoded data slice. In this instance, the DSTexecution unit having the corrupted encoded data slices retrieves atleast three encoded data slices (of contiguous data and of error codingdata) in the set from the other DST execution units (recall for thisexample, the pillar width is 5 and the decode threshold is 3). The DSTexecution unit decodes the retrieved data slices using the DS errorencoding parameters to recapture the corresponding data segment. The DSTexecution unit then re-encodes the data segment using the DS errorencoding parameters to rebuild the corrupted encoded data slice. Oncethe encoded data slice is rebuilt, the DST execution unit functions aspreviously described.

FIG. 13 is a schematic block diagram of an embodiment of an inbounddistributed storage and/or task (DST) processing section 82 of a DSTclient module coupled to DST execution units of a distributed storageand task network (DSTN) module via a network 24. The inbound DSTprocessing section 82 includes a de-grouping module 180, a DS (dispersedstorage) error decoding module 182, a data de-partitioning module 184, acontrol module 186, and a distributed task control module 188. Note thatthe control module 186 and/or the distributed task control module 188may be separate modules from corresponding ones of outbound DSTprocessing section or may be the same modules.

In an example of operation, the DST execution units have completedexecution of corresponding partial tasks on the corresponding slicegroupings to produce partial results 102. The inbound DST processingsection 82 receives the partial results 102 via the distributed taskcontrol module 188. The inbound DST processing section 82 then processesthe partial results 102 to produce a final result, or results 104. Forexample, if the task was to find a specific word or phrase within data,the partial results 102 indicate where in each of the prescribedportions of the data the corresponding DST execution units found thespecific word or phrase. The distributed task control module 188combines the individual partial results 102 for the correspondingportions of the data into a final result 104 for the data as a whole.

In another example of operation, the inbound DST processing section 82is retrieving stored data from the DST execution units (i.e., the DSTNmodule). In this example, the DST execution units output encoded dataslices 100 corresponding to the data retrieval requests. The de-groupingmodule 180 receives retrieved slices 100 and de-groups them to produceencoded data slices per data partition 122. The DS error decoding module182 decodes, in accordance with DS error encoding parameters, theencoded data slices per data partition 122 to produce data partitions120.

The data de-partitioning module 184 combines the data partitions 120into the data 92. The control module 186 controls the conversion ofretrieved slices 100 into the data 92 using control signals 190 to eachof the modules. For instance, the control module 186 providesde-grouping information to the de-grouping module 180, provides the DSerror encoding parameters to the DS error decoding module 182, andprovides de-partitioning information to the data de-partitioning module184.

FIG. 14 is a logic diagram of an example of a method that is executableby distributed storage and task (DST) client module regarding inboundDST processing. The method begins at step 194 where the DST clientmodule receives partial results. The method continues at step 196 wherethe DST client module retrieves the task corresponding to the partialresults. For example, the partial results include header informationthat identifies the requesting entity, which correlates to the requestedtask.

The method continues at step 198 where the DST client module determinesresult processing information based on the task. For example, if thetask were to identify a particular word or phrase within the data, theresult processing information would indicate to aggregate the partialresults for the corresponding portions of the data to produce the finalresult. As another example, if the task were to count the occurrences ofa particular word or phrase within the data, results of processing theinformation would indicate to add the partial results to produce thefinal results. The method continues at step 200 where the DST clientmodule processes the partial results in accordance with the resultprocessing information to produce the final result or results.

FIG. 15 is a diagram of an example of de-grouping selection processingof an inbound distributed storage and task (DST) processing section of aDST client module. In general, this is an inverse process of thegrouping module of the outbound DST processing section of FIG. 9.Accordingly, for each data partition (e.g., partition #1), thede-grouping module retrieves the corresponding slice grouping from theDST execution units (EU) (e.g., DST 1-5).

As shown, DST execution unit #1 provides a first slice grouping, whichincludes the first encoded slices of each of the sets of encoded slices(e.g., encoded data slices of contiguous data of data blocks 1-15); DSTexecution unit #2 provides a second slice grouping, which includes thesecond encoded slices of each of the sets of encoded slices (e.g.,encoded data slices of contiguous data of data blocks 16-30); DSTexecution unit #3 provides a third slice grouping, which includes thethird encoded slices of each of the sets of encoded slices (e.g.,encoded data slices of contiguous data of data blocks 31-45); DSTexecution unit #4 provides a fourth slice grouping, which includes thefourth encoded slices of each of the sets of encoded slices (e.g., firstencoded data slices of error coding (EC) data); and DST execution unit#5 provides a fifth slice grouping, which includes the fifth encodedslices of each of the sets of encoded slices (e.g., first encoded dataslices of error coding (EC) data).

The de-grouping module de-groups the slice groupings (e.g., receivedslices 100) using a de-grouping selector 180 controlled by a controlsignal 190 as shown in the example to produce a plurality of sets ofencoded data slices (e.g., retrieved slices for a partition into sets ofslices 122). Each set corresponding to a data segment of the datapartition.

FIG. 16 is a schematic block diagram of an embodiment of a dispersedstorage (DS) error decoding module 182 of an inbound distributed storageand task (DST) processing section. The DS error decoding module 182includes an inverse per slice security processing module 202, ade-slicing module 204, an error decoding module 206, an inverse segmentsecurity module 208, a de-segmenting processing module 210, and acontrol module 186.

In an example of operation, the inverse per slice security processingmodule 202, when enabled by the control module 186, unsecures eachencoded data slice 122 based on slice de-security information receivedas control information 190 (e.g., the compliment of the slice securityinformation discussed with reference to FIG. 6) received from thecontrol module 186. The slice security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRCverification, etc.), and/or any other type of digital security. Forexample, when the inverse per slice security processing module 202 isenabled, it verifies integrity information (e.g., a CRC value) of eachencoded data slice 122, it decrypts each verified encoded data slice,and decompresses each decrypted encoded data slice to produce sliceencoded data 158. When the inverse per slice security processing module202 is not enabled, it passes the encoded data slices 122 as the slicedencoded data 158 or is bypassed such that the retrieved encoded dataslices 122 are provided as the sliced encoded data 158.

The de-slicing module 204 de-slices the sliced encoded data 158 intoencoded data segments 156 in accordance with a pillar width of the errorcorrection encoding parameters received as control information 190 fromthe control module 186. For example, if the pillar width is five, thede-slicing module 204 de-slices a set of five encoded data slices intoan encoded data segment 156. The error decoding module 206 decodes theencoded data segments 156 in accordance with error correction decodingparameters received as control information 190 from the control module186 to produce secure data segments 154. The error correction decodingparameters include identifying an error correction encoding scheme(e.g., forward error correction algorithm, a Reed-Solomon basedalgorithm, an information dispersal algorithm, etc.), a pillar width, adecode threshold, a read threshold, a write threshold, etc. For example,the error correction decoding parameters identify a specific errorcorrection encoding scheme, specify a pillar width of five, and specifya decode threshold of three.

The inverse segment security processing module 208, when enabled by thecontrol module 186, unsecures the secured data segments 154 based onsegment security information received as control information 190 fromthe control module 186. The segment security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRC,etc.) verification, and/or any other type of digital security. Forexample, when the inverse segment security processing module 208 isenabled, it verifies integrity information (e.g., a CRC value) of eachsecure data segment 154, it decrypts each verified secured data segment,and decompresses each decrypted secure data segment to produce a datasegment 152. When the inverse segment security processing module 208 isnot enabled, it passes the decoded data segment 154 as the data segment152 or is bypassed.

The de-segment processing module 210 receives the data segments 152 andreceives de-segmenting information as control information 190 from thecontrol module 186. The de-segmenting information indicates how thede-segment processing module 210 is to de-segment the data segments 152into a data partition 120. For example, the de-segmenting informationindicates how the rows and columns of data segments are to be rearrangedto yield the data partition 120.

FIG. 17 is a diagram of an example of de-slicing and error decodingprocessing of a dispersed error decoding module. A de-slicing module 204receives at least a decode threshold number of encoded data slices 158for each data segment in accordance with control information 190 andprovides encoded data 156. In this example, a decode threshold is three.As such, each set of encoded data slices 158 is shown to have threeencoded data slices per data segment. The de-slicing module 204 mayreceive three encoded data slices per data segment because an associateddistributed storage and task (DST) client module requested retrievingonly three encoded data slices per segment or selected three of theretrieved encoded data slices per data segment. As shown, which is basedon the unity matrix encoding previously discussed with reference to FIG.8, an encoded data slice may be a data-based encoded data slice (e.g.,DS1_d1&d2) or an error code based encoded data slice (e.g., ES3_1).

An error decoding module 206 decodes the encoded data 156 of each datasegment in accordance with the error correction decoding parameters ofcontrol information 190 to produce secured segments 154. In thisexample, data segment 1 includes 3 rows with each row being treated asone word for encoding. As such, data segment 1 includes three words:word 1 including data blocks d1 and d2, word 2 including data blocks d16and d17, and word 3 including data blocks d31 and d32. Each of datasegments 2-7 includes three words where each word includes two datablocks. Data segment 8 includes three words where each word includes asingle data block (e.g., d15, d30, and d45).

FIG. 18 is a diagram of an example of de-segment processing of aninbound distributed storage and task (DST) processing. In this example,a de-segment processing module 210 receives data segments 152 (e.g.,1-8) and rearranges the data blocks of the data segments into rows andcolumns in accordance with de-segmenting information of controlinformation 190 to produce a data partition 120. Note that the number ofrows is based on the decode threshold (e.g., 3 in this specific example)and the number of columns is based on the number and size of the datablocks.

The de-segmenting module 210 converts the rows and columns of datablocks into the data partition 120. Note that each data block may be ofthe same size as other data blocks or of a different size. In addition,the size of each data block may be a few bytes to megabytes of data.

FIG. 19 is a diagram of an example of converting slice groups into data92 within an inbound distributed storage and task (DST) processingsection. As shown, the data 92 is reconstructed from a plurality of datapartitions (1-x, where x is an integer greater than 4). Each datapartition (or chunk set of data) is decoded and re-grouped using ade-grouping and decoding function 212 and a de-partition function 214from slice groupings as previously discussed. For a given datapartition, the slice groupings (e.g., at least a decode threshold perdata segment of encoded data slices) are received from DST executionunits. From data partition to data partition, the ordering of the slicegroupings received from the DST execution units may vary as discussedwith reference to FIG. 10.

FIG. 20 is a diagram of an example of a distributed storage and/orretrieval within the distributed computing system. The distributedcomputing system includes a plurality of distributed storage and/or task(DST) processing client modules 34 (one shown) coupled to a distributedstorage and/or task processing network (DSTN) module, or multiple DSTNmodules, via a network 24. The DST client module 34 includes an outboundDST processing section 80 and an inbound DST processing section 82. TheDSTN module includes a plurality of DST execution units. Each DSTexecution unit includes a controller 86, memory 88, one or moredistributed task (DT) execution modules 90, and a DST client module 34.

In an example of data storage, the DST client module 34 has data 92 thatit desires to store in the DSTN module. The data 92 may be a file (e.g.,video, audio, text, graphics, etc.), a data object, a data block, anupdate to a file, an update to a data block, etc. In this instance, theoutbound DST processing module 80 converts the data 92 into encoded dataslices 216 as will be further described with reference to FIGS. 21-23.The outbound DST processing module 80 sends, via the network 24, to theDST execution units for storage as further described with reference toFIG. 24.

In an example of data retrieval, the DST client module 34 issues aretrieve request to the DST execution units for the desired data 92. Theretrieve request may address each DST executions units storing encodeddata slices of the desired data, address a decode threshold number ofDST execution units, address a read threshold number of DST executionunits, or address some other number of DST execution units. In responseto the request, each addressed DST execution unit retrieves its encodeddata slices 100 of the desired data and sends them to the inbound DSTprocessing section 82, via the network 24.

When, for each data segment, the inbound DST processing section 82receives at least a decode threshold number of encoded data slices 100,it converts the encoded data slices 100 into a data segment. The inboundDST processing section 82 aggregates the data segments to produce theretrieved data 92.

FIG. 21 is a schematic block diagram of an embodiment of an outbounddistributed storage and/or task (DST) processing section 80 of a DSTclient module coupled to a distributed storage and task network (DSTN)module (e.g., a plurality of DST execution units) via a network 24. Theoutbound DST processing section 80 includes a data partitioning module110, a dispersed storage (DS) error encoding module 112, a groupingselector module 114, a control module 116, and a distributed taskcontrol module 118.

In an example of operation, the data partitioning module 110 isby-passed such that data 92 is provided directly to the DS errorencoding module 112. The control module 116 coordinates the by-passingof the data partitioning module 110 by outputting a bypass 220 messageto the data partitioning module 110.

The DS error encoding module 112 receives the data 92 in a serialmanner, a parallel manner, and/or a combination thereof. The DS errorencoding module 112 DS error encodes the data in accordance with controlinformation 160 from the control module 116 to produce encoded dataslices 218. The DS error encoding includes segmenting the data 92 intodata segments, segment security processing (e.g., encryption,compression, watermarking, integrity check (e.g., CRC, etc.)), errorencoding, slicing, and/or per slice security processing (e.g.,encryption, compression, watermarking, integrity check (e.g., CRC,etc.)). The control information 160 indicates which steps of the DSerror encoding are active for the data 92 and, for active steps,indicates the parameters for the step. For example, the controlinformation 160 indicates that the error encoding is active and includeserror encoding parameters (e.g., pillar width, decode threshold, writethreshold, read threshold, type of error encoding, etc.).

The grouping selector module 114 groups the encoded slices 218 of thedata segments into pillars of slices 216. The number of pillarscorresponds to the pillar width of the DS error encoding parameters. Inthis example, the distributed task control module 118 facilitates thestorage request.

FIG. 22 is a schematic block diagram of an example of a dispersedstorage (DS) error encoding module 112 for the example of FIG. 21. TheDS error encoding module 112 includes a segment processing module 142, asegment security processing module 144, an error encoding module 146, aslicing module 148, and a per slice security processing module 150. Eachof these modules is coupled to a control module 116 to receive controlinformation 160 therefrom.

In an example of operation, the segment processing module 142 receivesdata 92 and receives segmenting information as control information 160from the control module 116. The segmenting information indicates howthe segment processing module is to segment the data. For example, thesegmenting information indicates the size of each data segment. Thesegment processing module 142 segments the data 92 into data segments152 in accordance with the segmenting information.

The segment security processing module 144, when enabled by the controlmodule 116, secures the data segments 152 based on segment securityinformation received as control information 160 from the control module116. The segment security information includes data compression,encryption, watermarking, integrity check (e.g., CRC, etc.), and/or anyother type of digital security. For example, when the segment securityprocessing module 144 is enabled, it compresses a data segment 152,encrypts the compressed data segment, and generates a CRC value for theencrypted data segment to produce a secure data segment. When thesegment security processing module 144 is not enabled, it passes thedata segments 152 to the error encoding module 146 or is bypassed suchthat the data segments 152 are provided to the error encoding module146.

The error encoding module 146 encodes the secure data segments inaccordance with error correction encoding parameters received as controlinformation 160 from the control module 116. The error correctionencoding parameters include identifying an error correction encodingscheme (e.g., forward error correction algorithm, a Reed-Solomon basedalgorithm, an information dispersal algorithm, etc.), a pillar width, adecode threshold, a read threshold, a write threshold, etc. For example,the error correction encoding parameters identify a specific errorcorrection encoding scheme, specifies a pillar width of five, andspecifies a decode threshold of three. From these parameters, the errorencoding module 146 encodes a data segment to produce an encoded datasegment.

The slicing module 148 slices the encoded data segment in accordancewith a pillar width of the error correction encoding parameters. Forexample, if the pillar width is five, the slicing module slices anencoded data segment into a set of five encoded data slices. As such,for a plurality of data segments, the slicing module 148 outputs aplurality of sets of encoded data slices as shown within encoding andslicing function 222 as described.

The per slice security processing module 150, when enabled by thecontrol module 116, secures each encoded data slice based on slicesecurity information received as control information 160 from thecontrol module 116. The slice security information includes datacompression, encryption, watermarking, integrity check (e.g., CRC,etc.), and/or any other type of digital security. For example, when theper slice security processing module 150 is enabled, it may compress anencoded data slice, encrypt the compressed encoded data slice, andgenerate a CRC value for the encrypted encoded data slice to produce asecure encoded data slice tweaking. When the per slice securityprocessing module 150 is not enabled, it passes the encoded data slicesor is bypassed such that the encoded data slices 218 are the output ofthe DS error encoding module 112.

FIG. 23 is a diagram of an example of converting data 92 into pillarslice groups utilizing encoding, slicing and pillar grouping function224 for storage in memory of a distributed storage and task network(DSTN) module. As previously discussed the data 92 is encoded and slicedinto a plurality of sets of encoded data slices; one set per datasegment. The grouping selection module organizes the sets of encodeddata slices into pillars of data slices. In this example, the DS errorencoding parameters include a pillar width of 5 and a decode thresholdof 3. As such, for each data segment, 5 encoded data slices are created.

The grouping selection module takes the first encoded data slice of eachof the sets and forms a first pillar, which may be sent to the first DSTexecution unit. Similarly, the grouping selection module creates thesecond pillar from the second slices of the sets; the third pillar fromthe third slices of the sets; the fourth pillar from the fourth slicesof the sets; and the fifth pillar from the fifth slices of the set.

FIG. 24 is a schematic block diagram of an embodiment of a distributedstorage and/or task (DST) execution unit that includes an interface 169,a controller 86, memory 88, one or more distributed task (DT) executionmodules 90, and a DST client module 34. A computing core 26 may beutilized to implement the one or more DT execution modules 90 and theDST client module 34. The memory 88 is of sufficient size to store asignificant number of encoded data slices (e.g., thousands of slices tohundreds-of-millions of slices) and may include one or more hard drivesand/or one or more solid-state memory devices (e.g., flash memory, DRAM,etc.).

In an example of storing a pillar of slices 216, the DST execution unitreceives, via interface 169, a pillar of slices 216 (e.g., pillar #1slices). The memory 88 stores the encoded data slices 216 of the pillarof slices in accordance with memory control information 174 it receivesfrom the controller 86. The controller 86 (e.g., a processing module, aCPU, etc.) generates the memory control information 174 based ondistributed storage information (e.g., user information (e.g., user ID,distributed storage permissions, data access permission, etc.), vaultinformation (e.g., virtual memory assigned to user, user group, etc.),etc.). Similarly, when retrieving slices, the DST execution unitreceives, via interface 169, a slice retrieval request. The memory 88retrieves the slice in accordance with memory control information 174 itreceives from the controller 86. The memory 88 outputs the slice 100,via the interface 169, to a requesting entity.

FIG. 25 is a schematic block diagram of an example of operation of aninbound distributed storage and/or task (DST) processing section 82 forretrieving dispersed error encoded data 92. The inbound DST processingsection 82 includes a de-grouping module 180, a dispersed storage (DS)error decoding module 182, a data de-partitioning module 184, a controlmodule 186, and a distributed task control module 188. Note that thecontrol module 186 and/or the distributed task control module 188 may beseparate modules from corresponding ones of an outbound DST processingsection or may be the same modules.

In an example of operation, the inbound DST processing section 82 isretrieving stored data 92 from the DST execution units (i.e., the DSTNmodule). In this example, the DST execution units output encoded dataslices corresponding to data retrieval requests from the distributedtask control module 188. The de-grouping module 180 receives pillars ofslices 100 and de-groups them in accordance with control information 190from the control module 186 to produce sets of encoded data slices 218.The DS error decoding module 182 decodes, in accordance with the DSerror encoding parameters received as control information 190 from thecontrol module 186, each set of encoded data slices 218 to produce datasegments, which are aggregated into retrieved data 92. The datade-partitioning module 184 is by-passed in this operational mode via abypass signal 226 of control information 190 from the control module186.

FIG. 26 is a schematic block diagram of an embodiment of a dispersedstorage (DS) error decoding module 182 of an inbound distributed storageand task (DST) processing section. The DS error decoding module 182includes an inverse per slice security processing module 202, ade-slicing module 204, an error decoding module 206, an inverse segmentsecurity module 208, and a de-segmenting processing module 210. Thedispersed error decoding module 182 is operable to de-slice and decodeencoded slices per data segment 218 utilizing a de-slicing and decodingfunction 228 to produce a plurality of data segments that arede-segmented utilizing a de-segment function 230 to recover data 92.

In an example of operation, the inverse per slice security processingmodule 202, when enabled by the control module 186 via controlinformation 190, unsecures each encoded data slice 218 based on slicede-security information (e.g., the compliment of the slice securityinformation discussed with reference to FIG. 6) received as controlinformation 190 from the control module 186. The slice de-securityinformation includes data decompression, decryption, de-watermarking,integrity check (e.g., CRC verification, etc.), and/or any other type ofdigital security. For example, when the inverse per slice securityprocessing module 202 is enabled, it verifies integrity information(e.g., a CRC value) of each encoded data slice 218, it decrypts eachverified encoded data slice, and decompresses each decrypted encodeddata slice to produce slice encoded data. When the inverse per slicesecurity processing module 202 is not enabled, it passes the encodeddata slices 218 as the sliced encoded data or is bypassed such that theretrieved encoded data slices 218 are provided as the sliced encodeddata.

The de-slicing module 204 de-slices the sliced encoded data into encodeddata segments in accordance with a pillar width of the error correctionencoding parameters received as control information 190 from a controlmodule 186. For example, if the pillar width is five, the de-slicingmodule de-slices a set of five encoded data slices into an encoded datasegment. Alternatively, the encoded data segment may include just threeencoded data slices (e.g., when the decode threshold is 3).

The error decoding module 206 decodes the encoded data segments inaccordance with error correction decoding parameters received as controlinformation 190 from the control module 186 to produce secure datasegments. The error correction decoding parameters include identifyingan error correction encoding scheme (e.g., forward error correctionalgorithm, a Reed-Solomon based algorithm, an information dispersalalgorithm, etc.), a pillar width, a decode threshold, a read threshold,a write threshold, etc. For example, the error correction decodingparameters identify a specific error correction encoding scheme, specifya pillar width of five, and specify a decode threshold of three.

The inverse segment security processing module 208, when enabled by thecontrol module 186, unsecures the secured data segments based on segmentsecurity information received as control information 190 from thecontrol module 186. The segment security information includes datadecompression, decryption, de-watermarking, integrity check (e.g., CRC,etc.) verification, and/or any other type of digital security. Forexample, when the inverse segment security processing module is enabled,it verifies integrity information (e.g., a CRC value) of each securedata segment, it decrypts each verified secured data segment, anddecompresses each decrypted secure data segment to produce a datasegment 152. When the inverse segment security processing module 208 isnot enabled, it passes the decoded data segment 152 as the data segmentor is bypassed. The de-segmenting processing module 210 aggregates thedata segments 152 into the data 92 in accordance with controlinformation 190 from the control module 186.

FIG. 27 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module that includes aplurality of distributed storage and task (DST) execution units (#1through #n, where, for example, n is an integer greater than or equal tothree). Each of the DST execution units includes a DST client module 34,a controller 86, one or more DT (distributed task) execution modules 90,and memory 88.

In this example, the DSTN module stores, in the memory of the DSTexecution units, a plurality of DS (dispersed storage) encoded data(e.g., 1 through n, where n is an integer greater than or equal to two)and stores a plurality of DS encoded task codes (e.g., 1 through k,where k is an integer greater than or equal to two). The DS encoded datamay be encoded in accordance with one or more examples described withreference to FIGS. 3-19 (e.g., organized in slice groupings) or encodedin accordance with one or more examples described with reference toFIGS. 20-26 (e.g., organized in pillar groups). The data that is encodedinto the DS encoded data may be of any size and/or of any content. Forexample, the data may be one or more digital books, a copy of acompany's emails, a large-scale Internet search, a video security file,one or more entertainment video files (e.g., television programs,movies, etc.), data files, and/or any other large amount of data (e.g.,greater than a few Terra-Bytes).

The tasks that are encoded into the DS encoded task code may be a simplefunction (e.g., a mathematical function, a logic function, an identifyfunction, a find function, a search engine function, a replace function,etc.), a complex function (e.g., compression, human and/or computerlanguage translation, text-to-voice conversion, voice-to-textconversion, etc.), multiple simple and/or complex functions, one or morealgorithms, one or more applications, etc. The tasks may be encoded intothe DS encoded task code in accordance with one or more examplesdescribed with reference to FIGS. 3-19 (e.g., organized in slicegroupings) or encoded in accordance with one or more examples describedwith reference to FIGS. 20-26 (e.g., organized in pillar groups).

In an example of operation, a DST client module of a user device or of aDST processing unit issues a DST request to the DSTN module. The DSTrequest may include a request to retrieve stored data, or a portionthereof, may include a request to store data that is included with theDST request, may include a request to perform one or more tasks onstored data, may include a request to perform one or more tasks on dataincluded with the DST request, etc. In the cases where the DST requestincludes a request to store data or to retrieve data, the client moduleand/or the DSTN module processes the request as previously discussedwith reference to one or more of FIGS. 3-19 (e.g., slice groupings)and/or 20-26 (e.g., pillar groupings). In the case where the DST requestincludes a request to perform one or more tasks on data included withthe DST request, the DST client module and/or the DSTN module processthe DST request as previously discussed with reference to one or more ofFIGS. 3-19.

In the case where the DST request includes a request to perform one ormore tasks on stored data, the DST client module and/or the DSTN moduleprocesses the DST request as will be described with reference to one ormore of FIGS. 28-39. In general, the DST client module identifies dataand one or more tasks for the DSTN module to execute upon the identifieddata. The DST request may be for a one-time execution of the task or foran on-going execution of the task. As an example of the latter, as acompany generates daily emails, the DST request may be to daily searchnew emails for inappropriate content and, if found, record the content,the email sender(s), the email recipient(s), email routing information,notify human resources of the identified email, etc.

FIG. 28 is a schematic block diagram of an example of a distributedcomputing system performing tasks on stored data. In this example, twodistributed storage and task (DST) client modules 1-2 are shown: thefirst may be associated with a user device and the second may beassociated with a DST processing unit or a high priority user device(e.g., high priority clearance user, system administrator, etc.). EachDST client module includes a list of stored data 234 and a list of taskscodes 236. The list of stored data 234 includes one or more entries ofdata identifying information, where each entry identifies data stored inthe DSTN module 22. The data identifying information (e.g., data ID)includes one or more of a data file name, a data file directory listing,DSTN addressing information of the data, a data object identifier, etc.The list of tasks 236 includes one or more entries of task codeidentifying information, when each entry identifies task codes stored inthe DSTN module 22. The task code identifying information (e.g., taskID) includes one or more of a task file name, a task file directorylisting, DSTN addressing information of the task, another type ofidentifier to identify the task, etc.

As shown, the list of data 234 and the list of tasks 236 are eachsmaller in number of entries for the first DST client module than thecorresponding lists of the second DST client module. This may occurbecause the user device associated with the first DST client module hasfewer privileges in the distributed computing system than the deviceassociated with the second DST client module. Alternatively, this mayoccur because the user device associated with the first DST clientmodule serves fewer users than the device associated with the second DSTclient module and is restricted by the distributed computing systemaccordingly. As yet another alternative, this may occur through norestraints by the distributed computing system, it just occurred becausethe operator of the user device associated with the first DST clientmodule has selected fewer data and/or fewer tasks than the operator ofthe device associated with the second DST client module.

In an example of operation, the first DST client module selects one ormore data entries 238 and one or more tasks 240 from its respectivelists (e.g., selected data ID and selected task ID). The first DSTclient module sends its selections to a task distribution module 232.The task distribution module 232 may be within a stand-alone device ofthe distributed computing system, may be within the user device thatcontains the first DST client module, or may be within the DSTN module22.

Regardless of the task distribution module's location, it generates DSTallocation information 242 from the selected task ID 240 and theselected data ID 238. The DST allocation information 242 includes datapartitioning information, task execution information, and/orintermediate result information. The task distribution module 232 sendsthe DST allocation information 242 to the DSTN module 22. Note that oneor more examples of the DST allocation information will be discussedwith reference to one or more of FIGS. 29-39.

The DSTN module 22 interprets the DST allocation information 242 toidentify the stored DS encoded data (e.g., DS error encoded data 2) andto identify the stored DS error encoded task code (e.g., DS errorencoded task code 1). In addition, the DSTN module 22 interprets the DSTallocation information 242 to determine how the data is to bepartitioned and how the task is to be partitioned. The DSTN module 22also determines whether the selected DS error encoded data 238 needs tobe converted from pillar grouping to slice grouping. If so, the DSTNmodule 22 converts the selected DS error encoded data into slicegroupings and stores the slice grouping DS error encoded data byoverwriting the pillar grouping DS error encoded data or by storing itin a different location in the memory of the DSTN module 22 (i.e., doesnot overwrite the pillar grouping DS encoded data).

The DSTN module 22 partitions the data and the task as indicated in theDST allocation information 242 and sends the portions to selected DSTexecution units of the DSTN module 22. Each of the selected DSTexecution units performs its partial task(s) on its slice groupings toproduce partial results. The DSTN module 22 collects the partial resultsfrom the selected DST execution units and provides them, as resultinformation 244, to the task distribution module. The result information244 may be the collected partial results, one or more final results asproduced by the DSTN module 22 from processing the partial results inaccordance with the DST allocation information 242, or one or moreintermediate results as produced by the DSTN module 22 from processingthe partial results in accordance with the DST allocation information242.

The task distribution module 232 receives the result information 244 andprovides one or more final results 104 therefrom to the first DST clientmodule. The final result(s) 104 may be result information 244 or aresult(s) of the task distribution module's processing of the resultinformation 244.

In concurrence with processing the selected task of the first DST clientmodule, the distributed computing system may process the selectedtask(s) of the second DST client module on the selected data(s) of thesecond DST client module. Alternatively, the distributed computingsystem may process the second DST client module's request subsequent to,or preceding, that of the first DST client module. Regardless of theordering and/or parallel processing of the DST client module requests,the second DST client module provides its selected data 238 and selectedtask 240 to a task distribution module 232. If the task distributionmodule 232 is a separate device of the distributed computing system orwithin the DSTN module, the task distribution modules 232 coupled to thefirst and second DST client modules may be the same module. The taskdistribution module 232 processes the request of the second DST clientmodule in a similar manner as it processed the request of the first DSTclient module.

FIG. 29 is a schematic block diagram of an embodiment of a taskdistribution module 232 facilitating the example of FIG. 28. The taskdistribution module 232 includes a plurality of tables it uses togenerate distributed storage and task (DST) allocation information 242for selected data and selected tasks received from a DST client module.The tables include data storage information 248, task storageinformation 250, distributed task (DT) execution module information 252,and task

sub-task mapping information 246.

The data storage information table 248 includes a data identification(ID) field 260, a data size field 262, an addressing information field264, distributed storage (DS) information 266, and may further includeother information regarding the data, how it is stored, and/or how itcan be processed. For example, DS encoded data #1 has a data ID of 1, adata size of AA (e.g., a byte size of a few terra-bytes or more),addressing information of Addr_1_AA, and DS parameters of 3/5; SEG_1;and SLC_1. In this example, the addressing information may be a virtualaddress corresponding to the virtual address of the first storage word(e.g., one or more bytes) of the data and information on how tocalculate the other addresses, may be a range of virtual addresses forthe storage words of the data, physical addresses of the first storageword or the storage words of the data, may be a list of slice names ofthe encoded data slices of the data, etc. The DS parameters may includeidentity of an error encoding scheme, decode threshold/pillar width(e.g., 3/5 for the first data entry), segment security information(e.g., SEG_1), per slice security information (e.g., SLC_1), and/or anyother information regarding how the data was encoded into data slices.

The task storage information table 250 includes a task identification(ID) field 268, a task size field 270, an addressing information field272, distributed storage (DS) information 274, and may further includeother information regarding the task, how it is stored, and/or how itcan be used to process data. For example, DS encoded task #2 has a taskID of 2, a task size of XY, addressing information of Addr_2_XY, and DSparameters of 3/5; SEG_2; and SLC_2. In this example, the addressinginformation may be a virtual address corresponding to the virtualaddress of the first storage word (e.g., one or more bytes) of the taskand information on how to calculate the other addresses, may be a rangeof virtual addresses for the storage words of the task, physicaladdresses of the first storage word or the storage words of the task,may be a list of slices names of the encoded slices of the task code,etc. The DS parameters may include identity of an error encoding scheme,decode threshold/pillar width (e.g., 3/5 for the first data entry),segment security information (e.g., SEG_2), per slice securityinformation (e.g., SLC_2), and/or any other information regarding howthe task was encoded into encoded task slices. Note that the segmentand/or the per-slice security information include a type of encryption(if enabled), a type of compression (if enabled), watermarkinginformation (if enabled), and/or an integrity check scheme (if enabled).

The task

sub-task mapping information table 246 includes a task field 256 and asub-task field 258. The task field 256 identifies a task stored in thememory of a distributed storage and task network (DSTN) module and thecorresponding sub-task fields 258 indicates whether the task includessub-tasks and, if so, how many and if any of the sub-tasks are ordered.In this example, the task

sub-task mapping information table 246 includes an entry for each taskstored in memory of the DSTN module (e.g., task 1 through task k). Inparticular, this example indicates that task 1 includes 7 sub-tasks;task 2 does not include sub-tasks, and task k includes r number ofsub-tasks (where r is an integer greater than or equal to two).

The DT execution module table 252 includes a DST execution unit ID field276, a DT execution module ID field 278, and a DT execution modulecapabilities field 280. The DST execution unit ID field 276 includes theidentity of DST units in the DSTN module. The DT execution module IDfield 278 includes the identity of each DT execution unit in each DSTunit. For example, DST unit 1 includes three DT executions modules(e.g., 1_1, 1_2, and 1_3). The DT execution capabilities field 280includes identity of the capabilities of the corresponding DT executionunit. For example, DT execution module 1_1 includes capabilities X,where X includes one or more of MIPS capabilities, processing resources(e.g., quantity and capability of microprocessors, CPUs, digital signalprocessors, co-processor, microcontrollers, arithmetic logic circuitry,and/or any other analog and/or digital processing circuitry),availability of the processing resources, memory information (e.g.,type, size, availability, etc.), and/or any information germane toexecuting one or more tasks.

From these tables, the task distribution module 232 generates the DSTallocation information 242 to indicate where the data is stored, how topartition the data, where the task is stored, how to partition the task,which DT execution units should perform which partial task on which datapartitions, where and how intermediate results are to be stored, etc. Ifmultiple tasks are being performed on the same data or different data,the task distribution module factors such information into itsgeneration of the DST allocation information.

FIG. 30 is a diagram of a specific example of a distributed computingsystem performing tasks on stored data as a task flow 318. In thisexample, selected data 92 is data 2 and selected tasks are tasks 1, 2,and 3. Task 1 corresponds to analyzing translation of data from onelanguage to another (e.g., human language or computer language); task 2corresponds to finding specific words and/or phrases in the data; andtask 3 corresponds to finding specific translated words and/or phrasesin translated data.

In this example, task 1 includes 7 sub-tasks: task 1_1—identifynon-words (non-ordered); task 1_2—identify unique words (non-ordered);task 1_3—translate (non-ordered); task 1_4—translate back (ordered aftertask 1_3); task 1_5—compare to ID errors (ordered after task 1-4); task1_6 —determine non-word translation errors (ordered after task 1_5 and1_1); and task 1_7—determine correct translations (ordered after 1_5 and1_2). The sub-task further indicates whether they are an ordered task(i.e., are dependent on the outcome of another task) or non-order (i.e.,are independent of the outcome of another task). Task 2 does not includesub-tasks and task 3 includes two sub-tasks: task 3_1 translate; andtask 3_2 find specific word or phrase in translated data.

In general, the three tasks collectively are selected to analyze datafor translation accuracies, translation errors, translation anomalies,occurrence of specific words or phrases in the data, and occurrence ofspecific words or phrases on the translated data. Graphically, the data92 is translated 306 into translated data 282; is analyzed for specificwords and/or phrases 300 to produce a list of specific words and/orphrases 286; is analyzed for non-words 302 (e.g., not in a referencedictionary) to produce a list of non-words 290; and is analyzed forunique words 316 included in the data 92 (i.e., how many different wordsare included in the data) to produce a list of unique words 298. Each ofthese tasks is independent of each other and can therefore be processedin parallel if desired.

The translated data 282 is analyzed (e.g., sub-task 3_2) for specifictranslated words and/or phrases 304 to produce a list of specifictranslated words and/or phrases 288. The translated data 282 istranslated back 308 (e.g., sub-task 1_4) into the language of theoriginal data to produce re-translated data 284. These two tasks aredependent on the translate task (e.g., task 1_3) and thus must beordered after the translation task, which may be in a pipelined orderingor a serial ordering. The re-translated data 284 is then compared 310with the original data 92 to find words and/or phrases that did nottranslate (one way and/or the other) properly to produce a list ofincorrectly translated words 294. As such, the comparing task (e.g.,sub-task 1_5) 310 is ordered after the translation 306 andre-translation tasks 308 (e.g., sub-tasks 1_3 and 1_4).

The list of words incorrectly translated 294 is compared 312 to the listof non-words 290 to identify words that were not properly translatedbecause the words are non-words to produce a list of errors due tonon-words 292. In addition, the list of words incorrectly translated 294is compared 314 to the list of unique words 298 to identify unique wordsthat were properly translated to produce a list of correctly translatedwords 296. The comparison may also identify unique words that were notproperly translated to produce a list of unique words that were notproperly translated. Note that each list of words (e.g., specific wordsand/or phrases, non-words, unique words, translated words and/orphrases, etc.,) may include the word and/or phrase, how many times it isused, where in the data it is used, and/or any other informationrequested regarding a word and/or phrase.

FIG. 31 is a schematic block diagram of an example of a distributedstorage and task processing network (DSTN) module storing data and taskcodes for the example of FIG. 30. As shown, DS encoded data 2 is storedas encoded data slices across the memory (e.g., stored in memories 88)of DST execution units 1-5; the DS encoded task code 1 (of task 1) andDS encoded task 3 are stored as encoded task slices across the memory ofDST execution units 1-5; and DS encoded task code 2 (of task 2) isstored as encoded task slices across the memory of DST execution units3-7. As indicated in the data storage information table and the taskstorage information table of FIG. 29, the respective data/task has DSparameters of 3/5 for their decode threshold/pillar width; hencespanning the memory of five DST execution units.

FIG. 32 is a diagram of an example of distributed storage and task (DST)allocation information 242 for the example of FIG. 30. The DSTallocation information 242 includes data partitioning information 320,task execution information 322, and intermediate result information 324.The data partitioning information 320 includes the data identifier (ID),the number of partitions to split the data into, address information foreach data partition, and whether the DS encoded data has to betransformed from pillar grouping to slice grouping. The task executioninformation 322 includes tabular information having a taskidentification field 326, a task ordering field 328, a data partitionfield ID 330, and a set of DT execution modules 332 to use for thedistributed task processing per data partition. The intermediate resultinformation 324 includes tabular information having a name ID field 334,an ID of the DST execution unit assigned to process the correspondingintermediate result 336, a scratch pad storage field 338, and anintermediate result storage field 340.

Continuing with the example of FIG. 30, where tasks 1-3 are to bedistributedly performed on data 2, the data partitioning informationincludes the ID of data 2. In addition, the task distribution moduledetermines whether the DS encoded data 2 is in the proper format fordistributed computing (e.g., was stored as slice groupings). If not, thetask distribution module indicates that the DS encoded data 2 formatneeds to be changed from the pillar grouping format to the slicegrouping format, which will be done by the DSTN module. In addition, thetask distribution module determines the number of partitions to dividethe data into (e.g., 2_1 through 2_z) and addressing information foreach partition.

The task distribution module generates an entry in the task executioninformation section for each sub-task to be performed. For example, task1_1 (e.g., identify non-words on the data) has no task ordering (i.e.,is independent of the results of other sub-tasks), is to be performed ondata partitions 2_1 through 2_z by DT execution modules 1_1, 2_1, 3_1,4_1, and 5_1. For instance, DT execution modules 1_1, 2_1, 3_1, 4_1, and5_1 search for non-words in data partitions 2_1 through 2_z to producetask 1_1 intermediate results (R1-1, which is a list of non-words). Task1_2 (e.g., identify unique words) has similar task execution informationas task 1_1 to produce task 1_2 intermediate results (R1-2, which is thelist of unique words).

Task 1_3 (e.g., translate) includes task execution information as beingnon-ordered (i.e., is independent), having DT execution modules 1_1,2_1, 3_1, 4_1, and 5_1 translate data partitions 2_1 through 2_4 andhaving DT execution modules 1_2, 2_2, 3_2, 4_2, and 5_2 translate datapartitions 2_5 through 2_z to produce task 1_3 intermediate results(R1-3, which is the translated data). In this example, the datapartitions are grouped, where different sets of DT execution modulesperform a distributed sub-task (or task) on each data partition group,which allows for further parallel processing.

Task 1_4 (e.g., translate back) is ordered after task 1_3 and is to beexecuted on task 1_3's intermediate result (e.g., R1-3_1) (e.g., thetranslated data). DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1 areallocated to translate back task 1_3 intermediate result partitionsR1-3_1 through R1-3_4 and DT execution modules 1_2, 2_2, 6_1, 7_1, and7_2 are allocated to translate back task 1_3 intermediate resultpartitions R1-3_5 through R1-3_z to produce task 1-4 intermediateresults (R1-4, which is the translated back data).

Task _5 (e.g., compare data and translated data to identify translationerrors) is ordered after task 1_4 and is to be executed on task 1_4'sintermediate results (R4-1) and on the data. DT execution modules 1_1,2_1, 3_1, 4_1, and 5_1 are allocated to compare the data partitions (2_1through 2_z) with partitions of task 1-4 intermediate results partitionsR1-4_1 through R1-4_z to produce task 1_5 intermediate results (R1-5,which is the list words translated incorrectly).

Task 1_6 (e.g., determine non-word translation errors) is ordered aftertasks 1_1 and 1_5 and is to be executed on tasks 1_1's and 1_5'sintermediate results (R1-1 and R1-5). DT execution modules 1_1, 2_1,3_1, 4_1, and 5_1 are allocated to compare the partitions of task 1_1intermediate results (R1-1_1 through R1-1_z) with partitions of task 1-5intermediate results partitions (R1-5_1 through R1-5_z) to produce task1_6 intermediate results (R1-6, which is the list translation errors dueto non-words).

Task 1_7 (e.g., determine words correctly translated) is ordered aftertasks 1_2 and 1_5 and is to be executed on tasks 1_2's and 1_5'sintermediate results (R1-1 and R1-5). DT execution modules 1_2, 2_2,3_2, 4_2, and 5_2 are allocated to compare the partitions of task 1_2intermediate results (R1-2_1 through R1-2_z) with partitions of task 1-5intermediate results partitions (R1-5_1 through R1-5_z) to produce task1_7 intermediate results (R1-7, which is the list of correctlytranslated words).

Task 2 (e.g., find specific words and/or phrases) has no task ordering(i.e., is independent of the results of other sub-tasks), is to beperformed on data partitions 2_1 through 2_z by DT execution modules3_1, 4_1, 5_1, 6_1, and 7_1. For instance, DT execution modules 3_1,4_1, 5_1, 6_1, and 7_1 search for specific words and/or phrases in datapartitions 2_1 through 2_z to produce task 2 intermediate results (R2,which is a list of specific words and/or phrases).

Task 3_2 (e.g., find specific translated words and/or phrases) isordered after task 1_3 (e.g., translate) is to be performed onpartitions R1-3_1 through R1-3_z by DT execution modules 1_2, 2_2, 3_2,4_2, and 5_2. For instance, DT execution modules 1_2, 2_2, 3_2, 4_2, and5_2 search for specific translated words and/or phrases in thepartitions of the translated data (R1-3_1 through R1-3_z) to producetask 3_2 intermediate results (R3-2, which is a list of specifictranslated words and/or phrases).

For each task, the intermediate result information indicates which DSTunit is responsible for overseeing execution of the task and, if needed,processing the partial results generated by the set of allocated DTexecution units. In addition, the intermediate result informationindicates a scratch pad memory for the task and where the correspondingintermediate results are to be stored. For example, for intermediateresult R1-1 (the intermediate result of task 1_1), DST unit 1 isresponsible for overseeing execution of the task 1_1 and coordinatesstorage of the intermediate result as encoded intermediate result slicesstored in memory of DST execution units 1-5. In general, the scratch padis for storing non-DS encoded intermediate results and the intermediateresult storage is for storing DS encoded intermediate results.

FIGS. 33-38 are schematic block diagrams of the distributed storage andtask network (DSTN) module performing the example of FIG. 30. In FIG.33, the DSTN module accesses the data 92 and partitions it into aplurality of partitions 1-z in accordance with distributed storage andtask network (DST) allocation information. For each data partition, theDSTN identifies a set of its DT (distributed task) execution modules 90to perform the task (e.g., identify non-words (i.e., not in a referencedictionary) within the data partition) in accordance with the DSTallocation information. From data partition to data partition, the setof DT execution modules 90 may be the same, different, or a combinationthereof (e.g., some data partitions use the same set while other datapartitions use different sets).

For the first data partition, the first set of DT execution modules(e.g., 1_1, 2_1, 3_1, 4_1, and 5_1 per the DST allocation information ofFIG. 32) executes task 1_1 to produce a first partial result 102 ofnon-words found in the first data partition. The second set of DTexecution modules (e.g., 1_1, 2_1, 3_1, 4_1, and 5_1 per the DSTallocation information of FIG. 32) executes task 1_1 to produce a secondpartial result 102 of non-words found in the second data partition. Thesets of DT execution modules (as per the DST allocation information)perform task 1_1 on the data partitions until the “z” set of DTexecution modules performs task 1_1 on the “zth” data partition toproduce a “zth” partial result 102 of non-words found in the “zth” datapartition.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results toproduce the first intermediate result (R1-1), which is a list ofnon-words found in the data. For instance, each set of DT executionmodules 90 stores its respective partial result in the scratchpad memoryof DST execution unit 1 (which is identified in the DST allocation ormay be determined by DST execution unit 1). A processing module of DSTexecution 1 is engaged to aggregate the first through “zth” partialresults to produce the first intermediate result (e.g., R1_1). Theprocessing module stores the first intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the first intermediate result (e.g., the list ofnon-words). To begin the encoding, the DST client module determineswhether the list of non-words is of a sufficient size to partition(e.g., greater than a Terra-Byte). If yes, it partitions the firstintermediate result (R1-1) into a plurality of partitions (e.g., R1-1_1through R1-1_m). If the first intermediate result is not of sufficientsize to partition, it is not partitioned.

For each partition of the first intermediate result, or for the firstintermediate result, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-5).

In FIG. 34, the DSTN module is performing task 1_2 (e.g., find uniquewords) on the data 92. To begin, the DSTN module accesses the data 92and partitions it into a plurality of partitions 1-z in accordance withthe DST allocation information or it may use the data partitions of task1_1 if the partitioning is the same. For each data partition, the DSTNidentifies a set of its DT execution modules to perform task 1_2 inaccordance with the DST allocation information. From data partition todata partition, the set of DT execution modules may be the same,different, or a combination thereof. For the data partitions, theallocated set of DT execution modules executes task 1_2 to produce apartial results (e.g., 1^(st) through “zth”) of unique words found inthe data partitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results102 of task 1_2 to produce the second intermediate result (R1-2), whichis a list of unique words found in the data 92. The processing module ofDST execution 1 is engaged to aggregate the first through “zth” partialresults of unique words to produce the second intermediate result. Theprocessing module stores the second intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the second intermediate result (e.g., the list ofnon-words). To begin the encoding, the DST client module determineswhether the list of unique words is of a sufficient size to partition(e.g., greater than a Terra-Byte). If yes, it partitions the secondintermediate result (R1-2) into a plurality of partitions (e.g., R1-2_1through R1-2_m). If the second intermediate result is not of sufficientsize to partition, it is not partitioned.

For each partition of the second intermediate result, or for the secondintermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-5).

In FIG. 35, the DSTN module is performing task 1_3 (e.g., translate) onthe data 92. To begin, the DSTN module accesses the data 92 andpartitions it into a plurality of partitions 1-z in accordance with theDST allocation information or it may use the data partitions of task 1_1if the partitioning is the same. For each data partition, the DSTNidentifies a set of its DT execution modules to perform task 1_3 inaccordance with the DST allocation information (e.g., DT executionmodules 1_1, 2_1, 3_1, 4_1, and 5_1 translate data partitions 2_1through 2_4 and DT execution modules 1_2, 2_2, 3_2, 4_2, and 5_2translate data partitions 2_5 through 2_z). For the data partitions, theallocated set of DT execution modules 90 executes task 1_3 to producepartial results 102 (e.g., 1^(st) through “zth”) of translated data.

As indicated in the DST allocation information of FIG. 32, DST executionunit 2 is assigned to process the first through “zth” partial results oftask 1_3 to produce the third intermediate result (R1-3), which istranslated data. The processing module of DST execution 2 is engaged toaggregate the first through “zth” partial results of translated data toproduce the third intermediate result. The processing module stores thethird intermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 2.

DST execution unit 2 engages its DST client module to slice groupingbased DS error encode the third intermediate result (e.g., translateddata). To begin the encoding, the DST client module partitions the thirdintermediate result (R1-3) into a plurality of partitions (e.g., R1-3_1through R1-3_y). For each partition of the third intermediate result,the DST client module uses the DS error encoding parameters of the data(e.g., DS parameters of data 2, which includes 3/5 decodethreshold/pillar width ratio) to produce slice groupings. The slicegroupings are stored in the intermediate result memory (e.g., allocatedmemory in the memories of DST execution units 2-6 per the DST allocationinformation).

As is further shown in FIG. 35, the DSTN module is performing task 1_4(e.g., retranslate) on the translated data of the third intermediateresult. To begin, the DSTN module accesses the translated data (from thescratchpad memory or from the intermediate result memory and decodes it)and partitions it into a plurality of partitions in accordance with theDST allocation information. For each partition of the third intermediateresult, the DSTN identifies a set of its DT execution modules 90 toperform task 1_4 in accordance with the DST allocation information(e.g., DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1 are allocated totranslate back partitions R1-3_1 through R1-3_4 and DT execution modules1_2, 2_2, 6_1, 7_1, and 7_2 are allocated to translate back partitionsR1-3_5 through R1-3_z). For the partitions, the allocated set of DTexecution modules executes task 1_4 to produce partial results 102(e.g., 1^(st) through “zth”) of re-translated data.

As indicated in the DST allocation information of FIG. 32, DST executionunit 3 is assigned to process the first through “zth” partial results oftask 1_4 to produce the fourth intermediate result (R1-4), which isretranslated data. The processing module of DST execution 3 is engagedto aggregate the first through “zth” partial results of retranslateddata to produce the fourth intermediate result. The processing modulestores the fourth intermediate result as non-DS error encoded data inthe scratchpad memory or in another section of memory of DST executionunit 3.

DST execution unit 3 engages its DST client module to slice groupingbased DS error encode the fourth intermediate result (e.g., retranslateddata). To begin the encoding, the DST client module partitions thefourth intermediate result (R1-4) into a plurality of partitions (e.g.,R1-4_1 through R1-4_z). For each partition of the fourth intermediateresult, the DST client module uses the DS error encoding parameters ofthe data (e.g., DS parameters of data 2, which includes 3/5 decodethreshold/pillar width ratio) to produce slice groupings. The slicegroupings are stored in the intermediate result memory (e.g., allocatedmemory in the memories of DST execution units 3-7 per the DST allocationinformation).

In FIG. 36, a distributed storage and task network (DSTN) module isperforming task 1_5 (e.g., compare) on data 92 and retranslated data ofFIG. 35. To begin, the DSTN module accesses the data 92 and partitionsit into a plurality of partitions in accordance with the DST allocationinformation or it may use the data partitions of task 1_1 if thepartitioning is the same. The DSTN module also accesses the retranslateddata from the scratchpad memory, or from the intermediate result memoryand decodes it, and partitions it into a plurality of partitions inaccordance with the DST allocation information. The number of partitionsof the retranslated data corresponds to the number of partitions of thedata.

For each pair of partitions (e.g., data partition 1 and retranslateddata partition 1), the DSTN identifies a set of its DT execution modules90 to perform task 1_5 in accordance with the DST allocation information(e.g., DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1). For each pairof partitions, the allocated set of DT execution modules executes task1_5 to produce partial results 102 (e.g., 1^(st) through “zth”) of alist of incorrectly translated words and/or phrases.

As indicated in the DST allocation information of FIG. 32, DST executionunit 1 is assigned to process the first through “zth” partial results oftask 1_5 to produce the fifth intermediate result (R1-5), which is thelist of incorrectly translated words and/or phrases. In particular, theprocessing module of DST execution 1 is engaged to aggregate the firstthrough “zth” partial results of the list of incorrectly translatedwords and/or phrases to produce the fifth intermediate result. Theprocessing module stores the fifth intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 1.

DST execution unit 1 engages its DST client module to slice groupingbased DS error encode the fifth intermediate result. To begin theencoding, the DST client module partitions the fifth intermediate result(R1-5) into a plurality of partitions (e.g., R1-5_1 through R1-5_z). Foreach partition of the fifth intermediate result, the DST client moduleuses the DS error encoding parameters of the data (e.g., DS parametersof data 2, which includes 3/5 decode threshold/pillar width ratio) toproduce slice groupings. The slice groupings are stored in theintermediate result memory (e.g., allocated memory in the memories ofDST execution units 1-5 per the DST allocation information).

As is further shown in FIG. 36, the DSTN module is performing task 1_6(e.g., translation errors due to non-words) on the list of incorrectlytranslated words and/or phrases (e.g., the fifth intermediate resultR1-5) and the list of non-words (e.g., the first intermediate resultR1-1). To begin, the DSTN module accesses the lists and partitions theminto a corresponding number of partitions.

For each pair of partitions (e.g., partition R1-1_1 and partitionR1-5_1), the DSTN identifies a set of its DT execution modules 90 toperform task 1_6 in accordance with the DST allocation information(e.g., DT execution modules 1_1, 2_1, 3_1, 4_1, and 5_1). For each pairof partitions, the allocated set of DT execution modules executes task1_6 to produce partial results 102 (e.g., 1^(st) through “zth”) of alist of incorrectly translated words and/or phrases due to non-words.

As indicated in the DST allocation information of FIG. 32, DST executionunit 2 is assigned to process the first through “zth” partial results oftask 1_6 to produce the sixth intermediate result (R1-6), which is thelist of incorrectly translated words and/or phrases due to non-words. Inparticular, the processing module of DST execution 2 is engaged toaggregate the first through “zth” partial results of the list ofincorrectly translated words and/or phrases due to non-words to producethe sixth intermediate result. The processing module stores the sixthintermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 2.

DST execution unit 2 engages its DST client module to slice groupingbased DS error encode the sixth intermediate result. To begin theencoding, the DST client module partitions the sixth intermediate result(R1-6) into a plurality of partitions (e.g., R1-6_1 through R1-6_z). Foreach partition of the sixth intermediate result, the DST client moduleuses the DS error encoding parameters of the data (e.g., DS parametersof data 2, which includes 3/5 decode threshold/pillar width ratio) toproduce slice groupings. The slice groupings are stored in theintermediate result memory (e.g., allocated memory in the memories ofDST execution units 2-6 per the DST allocation information).

As is still further shown in FIG. 36, the DSTN module is performing task1_7 (e.g., correctly translated words and/or phrases) on the list ofincorrectly translated words and/or phrases (e.g., the fifthintermediate result R1-5) and the list of unique words (e.g., the secondintermediate result R1-2). To begin, the DSTN module accesses the listsand partitions them into a corresponding number of partitions.

For each pair of partitions (e.g., partition R1-2_1 and partitionR1-5_1), the DSTN identifies a set of its DT execution modules 90 toperform task 1_7 in accordance with the DST allocation information(e.g., DT execution modules 1_2, 2_2, 3_2, 4_2, and 5_2). For each pairof partitions, the allocated set of DT execution modules executes task1_7 to produce partial results 102 (e.g., 1^(st) through “zth”) of alist of correctly translated words and/or phrases.

As indicated in the DST allocation information of FIG. 32, DST executionunit 3 is assigned to process the first through “zth” partial results oftask 1_7 to produce the seventh intermediate result (R1-7), which is thelist of correctly translated words and/or phrases. In particular, theprocessing module of DST execution 3 is engaged to aggregate the firstthrough “zth” partial results of the list of correctly translated wordsand/or phrases to produce the seventh intermediate result. Theprocessing module stores the seventh intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 3.

DST execution unit 3 engages its DST client module to slice groupingbased DS error encode the seventh intermediate result. To begin theencoding, the DST client module partitions the seventh intermediateresult (R1-7) into a plurality of partitions (e.g., R1-7_1 throughR1-7_z). For each partition of the seventh intermediate result, the DSTclient module uses the DS error encoding parameters of the data (e.g.,DS parameters of data 2, which includes 3/5 decode threshold/pillarwidth ratio) to produce slice groupings. The slice groupings are storedin the intermediate result memory (e.g., allocated memory in thememories of DST execution units 3-7 per the DST allocation information).

In FIG. 37, the distributed storage and task network (DSTN) module isperforming task 2 (e.g., find specific words and/or phrases) on the data92. To begin, the DSTN module accesses the data and partitions it into aplurality of partitions 1-z in accordance with the DST allocationinformation or it may use the data partitions of task 1_1 if thepartitioning is the same. For each data partition, the DSTN identifies aset of its DT execution modules 90 to perform task 2 in accordance withthe DST allocation information. From data partition to data partition,the set of DT execution modules may be the same, different, or acombination thereof. For the data partitions, the allocated set of DTexecution modules executes task 2 to produce partial results 102 (e.g.,1^(st) through “zth”) of specific words and/or phrases found in the datapartitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 7 is assigned to process the first through “zth” partial results oftask 2 to produce task 2 intermediate result (R2), which is a list ofspecific words and/or phrases found in the data. The processing moduleof DST execution 7 is engaged to aggregate the first through “zth”partial results of specific words and/or phrases to produce the task 2intermediate result. The processing module stores the task 2intermediate result as non-DS error encoded data in the scratchpadmemory or in another section of memory of DST execution unit 7.

DST execution unit 7 engages its DST client module to slice groupingbased DS error encode the task 2 intermediate result. To begin theencoding, the DST client module determines whether the list of specificwords and/or phrases is of a sufficient size to partition (e.g., greaterthan a Terra-Byte). If yes, it partitions the task 2 intermediate result(R2) into a plurality of partitions (e.g., R2_1 through R2_m). If thetask 2 intermediate result is not of sufficient size to partition, it isnot partitioned.

For each partition of the task 2 intermediate result, or for the task 2intermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-4, and 7).

In FIG. 38, the distributed storage and task network (DSTN) module isperforming task 3 (e.g., find specific translated words and/or phrases)on the translated data (R1-3). To begin, the DSTN module accesses thetranslated data (from the scratchpad memory or from the intermediateresult memory and decodes it) and partitions it into a plurality ofpartitions in accordance with the DST allocation information. For eachpartition, the DSTN identifies a set of its DT execution modules toperform task 3 in accordance with the DST allocation information. Frompartition to partition, the set of DT execution modules may be the same,different, or a combination thereof. For the partitions, the allocatedset of DT execution modules 90 executes task 3 to produce partialresults 102 (e.g., 1^(st) through “zth”) of specific translated wordsand/or phrases found in the data partitions.

As indicated in the DST allocation information of FIG. 32, DST executionunit 5 is assigned to process the first through “zth” partial results oftask 3 to produce task 3 intermediate result (R3), which is a list ofspecific translated words and/or phrases found in the translated data.In particular, the processing module of DST execution 5 is engaged toaggregate the first through “zth” partial results of specific translatedwords and/or phrases to produce the task 3 intermediate result. Theprocessing module stores the task 3 intermediate result as non-DS errorencoded data in the scratchpad memory or in another section of memory ofDST execution unit 7.

DST execution unit 5 engages its DST client module to slice groupingbased DS error encode the task 3 intermediate result. To begin theencoding, the DST client module determines whether the list of specifictranslated words and/or phrases is of a sufficient size to partition(e.g., greater than a Terra-Byte). If yes, it partitions the task 3intermediate result (R3) into a plurality of partitions (e.g., R3_1through R3_m). If the task 3 intermediate result is not of sufficientsize to partition, it is not partitioned.

For each partition of the task 3 intermediate result, or for the task 3intermediate results, the DST client module uses the DS error encodingparameters of the data (e.g., DS parameters of data 2, which includes3/5 decode threshold/pillar width ratio) to produce slice groupings. Theslice groupings are stored in the intermediate result memory (e.g.,allocated memory in the memories of DST execution units 1-4, 5, and 7).

FIG. 39 is a diagram of an example of combining result information intofinal results 104 for the example of FIG. 30. In this example, theresult information includes the list of specific words and/or phrasesfound in the data (task 2 intermediate result), the list of specifictranslated words and/or phrases found in the data (task 3 intermediateresult), the list of non-words found in the data (task 1 firstintermediate result R1-1), the list of unique words found in the data(task 1 second intermediate result R1-2), the list of translation errorsdue to non-words (task 1 sixth intermediate result R1-6), and the listof correctly translated words and/or phrases (task 1 seventhintermediate result R1-7). The task distribution module provides theresult information to the requesting DST client module as the results104.

FIG. 40A is a schematic block diagram of an embodiment of a dispersedstorage system that includes user devices 14 of FIG. 1, a dispersedstorage (DS) processing module 350, and a dispersed storage network(DSN) memory 352. The DSN memory 352 includes one or more sets of DSunits 354. Each DS unit 354 may be implemented utilizing one or more ofa storage node, the distributed storage and task (DST) execution unit 36of FIG. 1, a storage server, a storage unit, a storage module, a memorydevice, a memory, a user device, the DST processing unit 16 of FIG. 1,and a DST processing module. The DS processing module 350 may beimplemented utilizing one or more of a server, a computer, the DS unit354, the user device 14, and the DST processing unit 16.

The system functions to store data from the user devices 14 in the DSNmemory 352 where the data is encrypted and encoded to producepluralities of non-redundant encoded data slices for storage in the atleast one set of DS units. The system further functions to retrieve thepluralities of non-redundant encoded data slices from the at least oneset of DS units to recover the data. In an example of storing the data,the user device 14 issues a store data request 356 to the DS processingmodule 350 to initiate a process to store the data in the DSN memory352. The store data request 356 includes one or more of the data, a datatag, and a data identifier of the data, where the user device generatesthe data tag based on performing at least one deterministic function onthe data. The operation of the user device 14 is discussed in greaterdetail with regards to FIGS. 40B and 40C.

The DS processing module 350 issues a store data response 358 to theuser device 14, where the store data response 358 includes a duplicatedata indicator. The DS processing module 350 generates the duplicatedata indicator to indicate whether the data has already been stored inthe DSN memory 352. The generating includes the DS processing module 350determining whether the data tag compares favorably to a retrieved datatag associated with data already stored in the DSN memory 352. The DSprocessing module 350 compares the data tag to a list of data tagsassociated with the data already stored in the DSN memory 352. The DSprocessing module 350 generates the duplicate data indicator to indicatethat the data has already been stored in the DSN memory 352 when thedata tag compares favorably (e.g., substantially the same) to a data tagof the list of data tags.

The user device 14 receives the store data response 358 and issuesanother store data request 356 that includes an encrypted key andfurther includes encrypted data of the data when the duplicate dataindicator indicates that the data is that duplicate data. The userdevice 14 generates the encrypted key by encrypting, with a private keyassociated with the user device, a key utilized to encrypt the data. Theuser device 14 performs a deterministic function on the data to producethe key utilized to encrypt the data. The DS processing module 350stores the encrypted key in a record-keeping mechanism associated withthe data including at least one of a directory, an index, a registry fora vault associated with the user device, as a data object in the DSNmemory 352, and a user record.

The DS processing module 350 stores the encrypted key in at least one ofa local memory of the DS processing module and the DSN memory 352 as aset of encoded encrypted key slices. For example, the DS processingmodule 350 encodes the encrypted key using a dispersed storage errorcoding function to produce the set of encoded encrypted key slices,generates a set of write slice requests 360 that includes the set ofencoded encrypted key slices, and outputs the set of write slicerequests 360 to the DSN memory 352. The DS processing module 350 mayreceive a set of write slice responses 362 from the DSN memory 352 withregards to the set of write slice requests 360 indicating a status ofthe set of write slice requests 360. When receiving the encrypted data,the DS processing module 350 stores the encrypted data in the DSN memory352 as a plurality of sets of encoded encrypted data slices. The DSprocessing module 350 encodes the encrypted data using the dispersedstorage error coding function to produce the plurality of sets ofencoded encrypted data slices.

In an example of retrieving the data, the user device 14 issues a readdata request 364 to the DS processing module 350, where the read datarequest 364 includes one or more of the data identifier and the datatag. The DS processing module 350 accesses the record-keeping mechanismassociated with the data to recover the encrypted key and accesses theDSN memory 352 to recover the encrypted data. For example, the DSprocessing module 350 issues a set of read slice requests 366 toretrieve the set of encoded encrypted key slices extracted from readslice responses 368 received from the DSN memory 352 and decodes atleast a decode threshold number of encoded encrypted key slices torecover the encrypted key. As another example, the DS processing module350 issues another set of read slice requests 366 to retrieve theplurality of sets of encoded encrypted data slices from the DSN memory352 and decodes at least a decode threshold number of encoded encrypteddata slices for each set of the plurality of sets to recover theencrypted data.

Having recovered the encrypted key and the encrypted data, the DSprocessing module 350 issues a read data response 370 to the user device14, where the read data response 370 includes the encrypted key and theencrypted data. The user device 14 decrypts the encrypted key using theprivate key of the user device to recover the key. The user device 14decrypts the encrypted data using the recovered key to produce recovereddata.

FIG. 40B is a schematic block diagram of the user device 14 of FIG. 1that includes a key generator 372, an encryptor 374, a data taggenerator 376, another encryptor 378, a store data module 380, aretrieve data module 382, a decryptor 384, and another decryptor 386.The user device 14 functions to securely access data 388 in a dispersedstorage network (DSN). The key generator 372 performs a deterministicfunction on the data 388 to generate a key 390. The deterministicfunction may include at least one of a hashing function, a cyclicredundancy code function, a mask generating function, and a hash basedmessage authentication code function.

The encryptor 374 encrypts the data 388 using the key 390 to generateencrypted data 392. The data tag generator 376 performs anotherdeterministic function on one or more of the key 390 and the encrypteddata 392 to produce a data tag 394. The other encryptor 378 encrypts thekey 390 using a private key 396 associated with the user device 14(e.g., a private key of a public-private key pair associated with theuser device) to produce an encrypted key 398. Alternatively, or inaddition to, the private key 396 may be associated with the data 388.For example, a private key list associates a plurality of dataidentifiers with a plurality of private keys. The user device 14 mayobtain the private key by at least one of retrieving the private key 396from a local memory, retrieving the private key 396 from a distributedauthentication system, receiving the private key 396 from a user input,and retrieving a private key 396 from the DSN.

When the user device 14 accesses the DSN to store the data 388 in theDSN, the store data module 380 issues a first store data request 400 tothe DSN, where the first store data request 400 includes one or more ofthe data tag 394 and a data identifier associated with the data 388.When the store data module 380 receives a store data response 402 fromthe DSN, the store data module 380 issues a second store data request400 to the DSN. The second store data request 400 includes the encryptedkey 398 and when the store data response 402 indicates that a duplicatecopy of the encrypted data does not exist within the DSN, the secondstore data request 400 includes the encrypted data 392.

When the user device 14 accesses the DSN to recover the data 388 fromthe DSN, the retrieve data module 382 issues a read data request 404 tothe DSN where the read data request 404 includes the data identifier.Alternatively, the read data request 404 includes the data tag 394associated with the data (e.g., when the user device 14 stores the datatag 394 in association with the data ID). The retrieve data module 382receives a read data response 406 that includes recovered encrypted data382 and a recovered encrypted key 398. The decryptor 384 decrypts therecovered encrypted key 398 using the private key 396 to produce arecovered key 390. The other decryptor 386 decrypts the recoveredencrypted data 392 using the recovered key 390 to produce recovered data388.

FIG. 40C is a flowchart illustrating an example of accessingnon-redundant data. The method begins at step 410 where a user devicegenerates a key based on data for storage in a dispersed storage network(DSN) memory. For example, the user device performs a deterministicfunction on the data to generate the key. The method continues at step412 where the user device encrypts the data using the key to produceencrypted data. The method continues at step 414 where the user devicegenerates a data tag based on the data. For example, the user deviceperforms another deterministic function on one or more of the key andencrypted data to generate the data tag. For instance, the user deviceperforms a mask generating function on the encrypted data to produce thedata tag. In another instance, a user device performs a hashing functionon the key to produce the data tag. In yet another instance, the userdevice performs the hashing function on the key to produce anintermediate value, performs the mask generating function on theencrypted data to produce another intermediate value, and performs anexclusive OR function on the intermediate value and the otherintermediate value to produce the data tag.

The method continues at step 416 where the user device encrypts the keyusing a private key associated with at least one of the user device andthe data to produce an encrypted key. The method continues at step 418where the user device issues a store data request that includes one ormore of the data tag, an identifier of the user device, and a dataidentifier of the data to a dispersed storage (DS) processing moduleassociated with the DSN memory. The method continues at step 420 wherethe DS processing module determines whether duplicate data of the datais stored in the DSN memory based on the data tag. The determiningincludes at least one of initiating a query, initiating a search,comparing the data tag to a data tag list, accessing a hierarchicalindex associated with storage of data objects in the DSN memory toidentify an index node for extraction of one or more store data tags,comparing the data tag to one or more data tags associated with datastored in the DSN memory. For example, the DS processing moduleindicates that the duplicate data of the data is stored in the DSNmemory when a retrieved data tag compares (e.g., substantially the same)favorably to the data tag. When duplicate data of the data is stored inthe DSN memory, the method branches to step 428. When duplicate data ofthe data is not stored in the DSN memory, the method continues to step422.

The method continues at step 422 where the DS processing module issues astore data response that indicates non-duplicate data to the user devicewhen the duplicate data of the data is not stored in the DSN memory. Themethod continues at step 424 where the user device issues another storedata request that includes the encrypted key and encrypted data to theDS processing module. The method continues at step 426 where the DSprocessing module stores the encrypted key and encrypted data in the DSNmemory. In addition, the DS processing module may update thehierarchical index to indicate that one or more of the user device andthe data is associated with DSN addresses utilized for storage of theencrypted key and encrypted data. The method branches to step 434.

When the duplicate data of the data is stored in the DSN memory, themethod continues at step 428 where the DS processing module issues astore data response that indicates duplicate data to the user device.The method continues at step 430 where the user device issues anotherstore data request that includes the encrypted key to the DS processingmodule. The method continues at step 432 where the DS processing modulestores the encrypted data in the DSN memory. In addition, the DSprocessing module may update the hierarchical index to indicate that oneor more of the user device and the data is associated with a DSNaddresses utilized for storage of the encrypted key and the duplicatedata (e.g., duplicate encrypted data).

When the user device accesses the DSN memory to recover the data, themethod continues at step 434 where the user device issues a read datarequest to the DS processing module where the read data request includesthe data identifier. The method continues at step 436 where the DSprocessing module issues a read data response to the user device thatincludes the encrypt key and the at least one of the duplicate data andthe encrypted data. The method continues at step 438 where the userdevice decrypts the encrypted key using the private key to produce arecovered key. The method continues at step 440 where the user devicedecrypts the at least one of the duplicate data and the encrypted datausing the recovered key to produce recovered data.

FIG. 41A is a schematic block diagram of a data encryption system thatincludes an analyzer 442, a manipulator 446, a key generator 444, anencryptor 448, and a storage module 450. The data encryption systemfunctions to securely store data 452 (e.g., in a dispersed storagenetwork (DSN) memory and/or a local memory). The analyzer 442 analyzesthe data 452 to determine a secure storage approach 454. The analyzingincludes determining a predictability level of the data 452. Forexample, the analyzer compresses the data 452 and indicates that thepredictability level of the data is high when a size of compressed datais less than a compression threshold value. As another example, theanalyzer 442 indicates that the predictability level of the data is highwhen a size of the data is less than a size threshold value.

The determining the secure storage approach includes producing theapproach 454 to indicate whether to generate a key 458 based on the data452 or a random number. For example, the analyzer 442 produces theapproach 454 to indicate to generate the key 458 based on the randomnumber when the predictability level of the data is high. As anotherexample, the analyzer 442 that produces the approach 454 indicates togenerate the key 458 based on the data when the predictability level ofthe data is low. When indicating to generate the key 458 based on thedata 452, the determining the secure storage approach may furtherinclude producing the approach 454 to indicate whether to manipulate thedata 452 prior to encrypting the data. For example, the analyzer 442produces the approach 454 to indicate to manipulate the data when thepredictability of the data is low and the size of the data is greaterthan the size threshold value.

The manipulator 446 manipulates the data 452 in accordance with theapproach to produce manipulated data 456. For example, the manipulator446 produces the manipulated data 456 to be substantially the same asthe data 452 when the approach indicates not to manipulate the data. Asanother example, the manipulator 446 pads up the data 452 to produce themanipulated data 456 when the approach indicates to manipulate the data.When padding the data 452, the manipulator 446 examines the current filesize and adds padding bytes to the end of the data 452 until a new datasize is that of a next highest rounded value. The rounded values may becalculated to never expand the data by more than 1%. This can be done bycalculating (log(file_size)/log(1+1%)), rounding that value up to thenext highest integer to get N, then calculating (1+1%)^N. The data ispadded to round up by adding the appropriate amount of padding bytes tomask its true size.

The key generator 444 generates the key 458 in accordance with theapproach 454. The key generator 444 generates the key 458 based on therandom number when the approach 454 indicates to utilize the randomnumber. The key generator 444 generates the key 458 based on one or moreof the data 452 and the manipulated data 456 in accordance with theapproach 454. The key generator 444 generates the key 458 based on oneor more of the data 452 and the manipulated data 456 by performing adeterministic function on one or more of the data 452 and themanipulated data 456 to produce the key 458. For example, key generator444 performs a hashing function on the data 452 to produce a datadigest, performs the hashing function on the manipulated data 456 toproduce a manipulated data digest, and performs a mask generatingfunction on the data digest and the manipulated data digest to producethe key 458.

The encryptor 448 encrypts the manipulated data 456 using the key 458 toproduce encrypted data 460. The storage module 450 facilitates storageof the encrypted data 460 and the key 458 in one or more of the localmemory and the DSN memory. For example, the storage module 450 sends theencrypted data 460 and the key 458 to a dispersed storage processingmodule associated with the DSN memory. As another example, the storagemodule 450 encodes the encrypted data 460 and the key 458 to produce aplurality of sets of slices, generates a plurality of sets of writeslice requests that includes the plurality of sets of slices, andoutputs the plurality of sets of write slice requests to the DSN memory.

FIG. 41B is a flowchart illustrating an example of securely storingdata. The method begins at step 462 where a processing module (e.g., ofa dispersed storage (DS) processing module) analyzes data for storage toproduce a data access risk level. The analyzing includes determining oneor more of a predictability level, a size, a data type, a source, anowner, a required data security level, a data access risk level, and adata sensitivity level. The method continues at step 464 where theprocessing module determines a secure storage approach based on the dataaccess risk level. The secure storage approach includes one of a highrisk approach, a medium risk approach, and a low risk approach. Forexample, the processing module selects the high risk approach when thedata access risk level is greater than a high risk threshold. As anotherexample, the processing module selects the medium risk approach when thedata access risk level is greater than a medium risk threshold and lessthan the high risk threshold. As yet another example, the processingmodule selects the low risk approach when the data access risk level isless than the medium risk threshold.

When the secure storage approach includes the high risk approach, themethod continues at step 466 where the processing module generates a keybased on a random number. The method branches to step 470 where theprocessing module encrypts the data using the key to produce encrypteddata. Next, the method branches to step 478 where the processing modulefacilitates storage of the key and encrypted data. The facilitatingincludes at least one of storing the key and encrypted data in a localmemory and storing the key and encrypted data in a dispersed storagenetwork memory.

When the secure storage approach includes the medium risk approach, themethod continues at step 468 where the processing module generates thekey based on the data. The generating includes performing adeterministic function on the data to produce the key. The methodbranches to step 470.

When the secure storage approach includes the low risk approach, themethod continues to step 472 where the processing module manipulates thedata in accordance with the secure storage approach to producemanipulated data. The manipulating of the data includes at least one ofpadding the data at the end of the data, padding the data at thebeginning of the data, interleaving portions of the data, andcompressing a portion of the data. The method continues at step 474where the processing module generates the key based on the manipulateddata. The generating includes performing a deterministic function on themanipulated data to produce the key. Alternatively, the processingmodule performs a deterministic function on the data and the manipulateddata to produce the key. The method continues at step 476 where theprocessing module encrypts the manipulated data using the key to producethe encrypted data. The method branches to step 478.

FIG. 42A is a schematic block diagram of another distributed storage andtask (DST processing unit 16 that includes a plurality of centralprocessing units (CPUs) 480 and a plurality of memories 54 of FIG. 2.Each CPU 480 is operably coupled to one or more memories of theplurality of memories 54 to provide access for storage and retrieval ofintermediate data associated with one or more processing threadsavailable to the CPU 480. From time to time, at least one processingthread of the one or more processing threads may be utilized to encodedata using a dispersed storage error coding function to produce one ormore sets of encoded data slices 488.

The access may be in accordance with a variety of performance levelsbased on one or more of configuration information, performancerestraints, hardware interfaces, loading levels, bus bandwidth, serialinterface bandwidth, and hardware architecture. Each CPU of theplurality of CPUs may have high-performance access 484 to at least onememory device 54 of the plurality of memory devices. The each CPU haslow performance access 486 for remaining memory devices 54 of theplurality of memory devices.

In an example of operation, a first CPU 480 of the plurality of CPUsreceives data 482 for encoding into the set of encoded data slices 488.The first CPU 480 allocates a memory address range for utilization by aprocessing thread to encode the data 482. The first CPU 480 identifies amemory 54 of the plurality of memories that is associated with theallocated memory address range (e.g., based on a lookup). The first CPU480 identifies associated available CPUs 480 associated with theidentified memory 54. The first CPU 480 selects a second CPU 480 of theassociated available CPUs based on an access performance level of eachof the associated CPUs with regards to the identified memory. Forexample, the first CPU 480 selects the second CPU 480 when the secondCPU has high-performance access 484 to the identified memory 54. Thefirst CPU 480 transfers the data 482 to the second CPU 480. The secondCPU 480 utilizes a processing thread of the second CPU to encode thedata 482 using the dispersed storage error coding function to producethe set of encoded data slices 488. The second CPU 480 outputs the setof encoded data slices 488.

Alternatively, or in addition to, the first CPU 480 distributes aportion of the data 482 to one or more other CPUs 480 of the pluralityof CPUs to facilitate parallel processing of the encoding of the data482. For example, the first CPU 480 distributes a first portion of thedata and a portion of an encoding matrix utilized in the dispersedstorage error encoding of the data to a third CPU 480 such that thethird CPU dispersed storage error encodes the first portion of the datausing the portion of the encoding matrix to produce a correspondingportion of the set of encoded data slices 488.

FIG. 42B is a flowchart illustrating an example of assigning processingresources. The method begins at step 490 where a processing module(e.g., of a dispersed storage (DS) processing module) allocates a memoryaddress range for utilization by a processing thread to encode data. Theprocessing module may assign an amount of memory commensurate with anencoding algorithm utilized to encode the data. The method continues atstep 492 where the processing module identifies a memory associated withthe memory address range. For example, the processing module performs alookup in an address range to memory device list based on the memoryaddress range to identify the memory. The method continues at step 494where the processing module identifies associated available centralprocessing units (CPUs) of a plurality of CPUs associated with thememory (e.g., operably coupled via high-performance access paths and/orlow performance access paths). The identifying includes at least one ofperforming a lookup in an association list, initiating a test,performing a query, and receiving a message.

The method continues at step 496 where the processing module selects aCPU of the associated available CPUs based on an access performancelevel of each of the associated available CPUs with regards to thememory. For example, the processing module selects a CPU of theassociated available CPUs when the tenth CPU is associated withhigh-performance access to the identified memory. The method continuesat step 498 where the processing module assigns a processing thread ofthe selected CPU to facilitate encoding of the data to produce at leastone set of encoded data slices using a dispersed storage error codingfunction. Alternatively, or in addition to, the processing moduledistributes one or more of a portion of the data and a portion of anencoding matrix of the dispersed storage error coding function to one ormore other CPUs of the associated available CPUs to facilitate parallelprocessing of encoding of the data to produce the at least one set ofencoded data slices.

FIG. 43A is a schematic block diagram of a dispersed storage network(DSN) memory 500 that includes a plurality of the dispersed storage (DS)units 354 of FIG. 40A. The plurality of DS units 354 includes at leastone DS unit set that includes a DS unit 354 and other DS units 502 ofthe DS unit set. The DS unit 354 includes a controller 504, a pluralityof main memories 506, and a plurality of internal integrity memories508. The DSN memory 500 functions to rebuild an encoded data slice to berebuilt, where the encoded data slice to be rebuilt is associated with amain memory 506 of the plurality of main memories. Data is encoded usingat least one of a dispersed storage error coding function and aredundant array of independent disks (RAID) coding function to producerebuilding information, where recovery of the encoded data slice to berebuilt is enabled by retrieving a threshold number of rebuildingelements of the rebuilding information. The rebuilding elements includesone or more of parity information and other encoded data slices of a setof encoded data slices that includes the encoded data slice to berebuilt.

In an example of operation, the controller 504 identifies the encodeddata slice to be rebuilt. The identifying includes a variety ofapproaches. A first approach includes indicating that the encoded dataslice to be rebuilt requires rebuilding when a calculated integrityvalue of the encoded data slice to be rebuilt compares unfavorably to aretrieved integrity value associated with the encoded data slice to berebuilt, where the retrieved integrity value is retrieved from anassociated internal integrity memory. A second approach includesreceiving an error message that includes an identifier of the encodeddata slice to be rebuilt. A third approach includes receiving arebuilding request that includes the identifier of the encoded dataslice to be rebuilt.

Having identified the encoded data slice to be rebuilt, the controller504 selects a rebuilding approach as one of an internal approach and anexternal approach. The selecting may be based on one or more of networktraffic level, a main memory availability indicator, an internalintegrity memory availability indicator, a number of available other DSunits of the DS unit set, a performance requirement, estimated networktraffic costs, a controller loading level, available control resources,and an active rebalancing operation status. The internal approach isassociated with utilizing rebuilding information from at least athreshold number of internal integrity memories of the plurality ofinternal integrity memories. The external approach is associated withutilizing rebuilding information from at least a threshold number ofother DS units of the DS unit set. For example, the controller 504selects the internal approach when estimated network traffic costs aregreater than a cost threshold. As another example, the controller 504selects the external approach when the controller loading level isgreater than a loading level threshold.

When the selected rebuilding approach includes the internal approach,the controller 504 retrieves a threshold number of rebuilding elementsfrom the threshold number of internal integrity memories 508. Forexample, the controller 504 retrieves a threshold number of data blocksand/or parity blocks of a common data slice that includes the encodeddata slice to be rebuilt when the RAID function is utilized. As anotherexample, the controller 504 retrieves a threshold number of encoded dataslices of the set of encoded data slices that includes the encoded dataslice to be rebuilt from the threshold number of internal integritymemories 508 when the dispersed storage error coding function isutilized. The controller 504 decodes the threshold number of rebuildingelements to produce a rebuilt encoded data slice.

When the selected rebuilding approach includes the external approach,the controller 504 retrieves the threshold number of rebuilding elementsfrom the threshold number of other DS units of the DS unit set 502. Forexample, the controller 504 issues read slice requests 510 and receivesread slice responses 512 to retrieve the threshold number of encodeddata slices of the set of encoded data slices that includes the encodeddata slice to be rebuilt from the threshold number of other DS units ofthe DS unit set when the dispersed storage error coding function isutilized. The controller decodes the threshold number of rebuildingelements to produce the rebuilt encoded data slice.

FIG. 43B is a flowchart illustrating an example of rebuilding a slice tobe rebuilt. The method begins at step 514 where a processing module(e.g., of a dispersed storage (DS) processing module) identifies a sliceto be rebuilt associated with a DS unit. The identifying includes atleast one of receiving an error message, comparing storage integrityinformation to calculated integrity information, and comparing a slicename list from the DS unit and from other DS units of a DS unit set thatincludes the DS unit. The method continues at step 516 where theprocessing module obtains DS unit status information. The DS unit statusinformation includes one or more of a network traffic level, a number ofavailable other DS units of the DS unit set, estimated network trafficcosts, a loading level of the DS unit, available resources of the DSunit, and active operation types of the DS unit.

The method continues at step 518 where the processing module selects arebuilding approach based on the DS unit status information. Therebuilding approach includes one of an internal approach and an externalapproach. The internal approach is associated with utilizing rebuildinginformation from one or more memories (e.g., a threshold number) of theDS unit. The external approach is associated with utilizing rebuildinginformation from at least a threshold number of other DS units of the DSunit set where data is encoded using a dispersed storage error codingfunction to produce a set of encoded data slices, including the encodeddata slice to be rebuilt, that are stored in the DS unit set. The methodbranches to step 524 when the processing module selects the externalapproach. The method continues to step 520 when the processing moduleselects the internal approach.

The method continues at step 520 where the processing module obtainsinternal rebuilding information from one or more memories of the DS unitwhen the internal approach is selected. The internal rebuildinginformation includes at least one of a threshold number of encoded dataslices of the set of encoded data slices when the dispersed storageerror coding function is utilized and a threshold number of data blocksand parity blocks when a redundant array of independent disks (RAID)function is utilized. For example, the processing module retrieves thethreshold number of data blocks and parity blocks from a thresholdnumber of memories of the DS unit when the RAID function is utilized. Asanother example, the processing module retrieves the threshold number ofencoded data slices from the threshold number of memories of the DS unitwhen the dispersed storage error coding function is utilized. Thedispersed storage error coding function and the RAID function may beutilized in accordance with a storage approach. The processing modulemay further determine the storage approach based on one or more ofreceiving the storage approach, a lookup, and selecting the storageapproach based on storage requirements when initially storing data.

The method continues at step 522 where the processing module rebuildsthe encoded data slice to be rebuilt utilizing the internal rebuildinginformation. For example, the processing module decodes the retrievedthreshold number of encoded data slices using the dispersed storageerror coding function to produce a rebuilt slice. As another example,the processing module utilizes the RAID function on the threshold numberof data blocks and parity blocks to produce the rebuilt slice.

The method continues at step 524 where the processing module obtainsexternal rebuilding information from at least a decode threshold numberof other DS units of the set of DS units that includes the DS unit whenthe processing module selects the external approach. The obtainingincludes issuing at least a decode threshold number of reads slicerequests to the other DS units and receiving at least a decode thresholdnumber of read slice responses. The method continues at step 526 wherethe processing module rebuilds the slice to be rebuilt utilizing theexternal rebuilding information. For example, the processing moduledecodes at least a decode threshold number of encoded data slices fromthe at least a decode threshold number of received read slice responsesto produce the slice to be rebuilt.

FIG. 44A is a schematic block diagram of another embodiment of adispersed storage system that includes the user device 14 of FIG. 1, thedispersed storage (DS) processing module 350 of FIG. 40A, and thedispersed storage network (DSN) memory 352 of FIG. 40A. The DSN memory352 includes one or more sets of DS units 354 of FIG. 40A. The systemfunctions to provide the user device 14 access to data stored in the DSNmemory 352. The user device 14 issues a store data request 530 to the DSprocessing module 350 to initiate a process to store the data in the DSNmemory 352. The store data request 530 includes the data and a dataidentifier of the data. The DS processing module 350 encodes the datausing a dispersed storage error coding function to produce a pluralityof sets of encoded data slices. The DS processing module 350 generates aplurality of sets of primary slice names based on a primary source name.The DS processing module 350 generates the primary source name based onat least one of applying a deterministic function to the data identifierand utilizing a pseudorandom function.

The DS processing module 350 issues one or more sets of primary writeslice requests 532 to the DSN memory 352 that includes the plurality ofsets of primary slice names and the plurality of sets of encoded dataslices. The DS processing module 350 receives one or more sets ofprimary write slice responses 534 from the DSN memory 352 indicatingstatus of storing the plurality of sets of encoded data slices. The DSprocessing module updates an index to associate the data identifier withthe primary source name.

The DS processing module 350 generates a plurality of sets of secondaryslice names based on a secondary source name. For example, the DSprocessing module applies a deterministic function to the primary sourcename to produce the secondary source name. The DS processing module 350issues one or more sets of secondary write slice requests 536 to the DSNmemory 352 that includes the plurality of sets of secondary slice namesand the plurality of sets of encoded data slices. The DS processingmodule 350 receives one or more sets of secondary write slice responses538 from the DSN memory 352 indicating status of storing the pluralityof sets of encoded data slices. The DS processing module 350 updates theindex to associate the data identifier with the secondary source name.The DS processing module 350 issues a store data response 540 to theuser device 14 indicating a status with regards to the process to storethe data in the DSN memory 352 based on the one or more sets ofsecondary write slice responses 538 and one or more sets of primarywrite slice responses 534.

The user device 14 issues a read data request 542 to the DS processingmodule 350 to initiate a process to retrieve the data from the DSNmemory 352. The read data request 542 includes the data identifier. TheDS processing module 350 recovers the primary source name and thesecondary source name from the index based on the data identifier of theread data request 542. The DS processing module 350 selects at least oneof the primary source name and the secondary source name based on one ormore of a system loading indicator, a predetermination, a request, asecurity indicator, a performance indicator, a DS unit set identifierassociated with the primary source name, a DS unit set identifierassociated with the secondary source name, a DS unit availabilityindicator, and a DSN memory availability indicator. For example, the DSprocessing module 350 selects the secondary source name when more DSunits of a DS unit set associated with the secondary source name areavailable as compared to available DS units of a DS unit set associatedwith the primary source name.

The DS processing module 350 issues one or more of primary read slicerequests 544 and secondary read slice requests 548 to the DSN memory 352to initiate recovery of the data. The DS processing module 350 receivesone or more of primary read slice responses 546 and secondary read sliceresponses 550 to produce received encoded data slices. The DS processingmodule 350 decodes the received encoded data slices to recover the data.The DS processing module 350 issues a read data response 552 to the userdevice 14 that includes the recovered data.

FIG. 44B is a flowchart illustrating an example of replicating data. Fora write sequence, a method begins at step 554 where a processing module(e.g., of a dispersed storage (DS) processing module) encodes data forstorage in a dispersed storage network (DSN) memory to produce aplurality of sets of encoded data slices. The method continues at step556 where the processing module generates a primary source name. Thegenerating includes at least one of generating the primary source namepseudo-randomly and performing a deterministic function on a dataidentifier associated with the data. For example, the processing moduleaccesses a registry based on the data identifier to recover a vaultidentifier and generates the primary source name to include the vaultidentifier and a pseudo-randomly generated object number. The methodcontinues at step 558 where the processing module generates a pluralityof sets of primary slice names based on the primary source name. Forexample, the processing module identifies a pillar width from theregistry and generates slice index fields of the plurality of sets ofprimary slice names based on the pillar width.

The method continues at step 560 where the processing module issues oneor more sets of primary write slice requests to the DSN memory thatincludes the plurality of sets of primary slice names and the pluralityof sets of encoded data slices. The issuing includes generating andoutputting the one or more sets of primary write slice requests. Themethod continues at step 562 where the processing module generates oneor more other source names based on the primary source name. Theprocessing module determines a number of the one or more other sourcenames based on one or more of a request, a message, a reliability goal,a performance goal, a cost goal, a predetermination, a size of the data,a network loading level, a security goal, and a lookup. For example, theprocessing module determines a higher than average number of the one ormore other source names when a security goal is higher than an averagesecurity goal level. The generating includes performing a deterministicfunction on the primary source name to generate each of the one or moreother source names. For example, the processing module performs a maskgenerating function on the primary source name to generate a primaryresult. Next, the processing module adds a first offset to the primaryresult to produce a first source name of the one or more other sourcenames. Next, the processing module adds a second offset to the primaryresult to produce a second source name of the one or more other sourcenames, etc.

For each other source name of the one or more other source names, themethod continues at step 564 where the processing module generates acorresponding plurality of sets of other slice names. For example, theprocessing module replaces the primary source name of a source namefield of the plurality of sets of primary slice names with the othersource name of the one or more source names to produce the correspondingplurality of sets of other slice names. For each corresponding pluralityof sets of other slice names, the method continues at step 566 where theprocessing module issues one or more sets of other write slice requeststo the DSN memory that includes the corresponding plurality of sets ofother slice names and the plurality of sets of encoded data slices. Theissuing includes generating and outputting the one or more sets of otherwrite slice requests. The method continues at step 568 where theprocessing module updates a hierarchical index to associate a dataidentifier of the data with the primary source name and each of the oneor more other source names. The updating includes at least one ofmodifying an existing entry of the hierarchical index and generating anew entry for the hierarchical index.

In an example of operation of a read sequence, the method continues orbegins at step 570 where the processing module receives a read datarequest that includes the data identifier. The method continues at step572 where the processing module identifies the primary source name andthe one or more other source names based on accessing the hierarchicalindex using the data identifier. The identifying includes extractingassociation information from at least one hierarchical index entryassociated with the data identifier. The method continues at step 574where the processing module selects at least one of the primary sourcename and the one or more other source names to produce one or moreselected source names. The selecting includes identifying a number ofsource names based on one or more of a performance requirement, asecurity requirement, a reliability requirement, an expected size of thedata, a network loading level, and a predetermination. For example, theprocessing module selects a higher than average number of source nameswhen the performance requirement indicates a higher than averagerequired performance level.

The method continues at step 576 where the processing module issues oneor more sets of read slice requests to the DSN memory based on the oneor more selected source names. The issuing includes generating andoutputting the one or more sets of read slice requests. The methodcontinues at step 578 where the processing module decodes receivedslices to reproduce the data. The decoding includes, for each of the oneor more sets of read slice requests, decoding at least a decodethreshold number of slices for each set of a corresponding plurality ofsets of read slice responses using a dispersed storage error codingfunction to produce a corresponding data segment for aggregation amongsta plurality of data segments to reproduce the data. Alternatively, or inaddition to, the processing module may simultaneously decode two or morecopies of the data by utilizing two or more source names in retrievingslices from the DSN memory. The processing module may stop the decodingof the received slices when sufficient received slices have been decodedto reproduce the data.

FIG. 45A is a schematic block diagram of another embodiment of adispersed storage system that includes the user device 14 of FIG. 1, thedispersed storage (DS) processing module 350 of FIG. 40A, and the DSNmemory 352 of FIG. 40A. The DSN memory 352 includes a set of DS units354 of FIG. 40A. The system functions to utilize the set of DS units 354to facilitate a random write process. In an example of operation, theuser device 14 issues an open write file request 580 to the DSprocessing module 350 to initiate a write data process. The open writefile request 580 may include one or more of a data file for storage inthe set of DS units 354, a data identifier of the data file, a data sizeindicator of the data file, one or more data file offset indicatorsassociated with one or more data strings of the data file, and an updatelikelihood indicator for at least one data file offset of the one ormore data offset indicators. The DS processing module 350 partitions thedata file into a plurality of data segments in accordance with at leastone of at least some of the data file offsets and the data sizeindicator of the data file. For example, the DS processing module 350partitions the data file into 15 data segments when the one or more datafile offset indicators includes 15 indicators.

The DS processing module 350 temporarily stores at least some of theplurality of data segments in a local memory associated with the DSprocessing module 350. The DS processing module 350 stores remainingdata segments of the plurality of data segments in the DSN memory 352.The DS processing module 350 may select which of the plurality of datasegments to store in the local memory based on the update likelihoodindicator. For example, the DS processing module 350 stores 5 of the 15data segments in the local memory and stores a remaining 10 datasegments in the DSN memory 352.

When storing a remaining data segment in the DSN memory 352, the DSprocessing module 350 encodes each remaining data segment using adispersed storage error coding function to produce a set of encodedremaining slices and issues a set of write slice requests 582 to the setof DS units 354 that includes the set of encoded remaining slices and acommon transaction number. The DS processing module 350 receives writeslice responses 584 from the DSN memory 352 with regards to status ofthe set of write slice requests 582 (e.g., storage success or error).The DS processing module 350 issues a open write file response 586 tothe user device 14. The open write file response 586 may include one ormore of data segment identifiers of data segments of the plurality ofdata segments that are available for random writes and which remainingdata segments of the plurality of data segments have been currentlywritten to the DSN memory 352.

When updating a portion of the data file, the user device 14 issues arandom write data request 588 to the DS processing module 350 thatincludes one or more of the data identifier, an updated portion of thedata file, and an offset indicator corresponding to the updated portionof the data file. The DS processing module 350 updates a portion of thetemporarily stored data file with the updated portion of the data file.The updating includes one or more of appending, interleaving,overwriting, and locally storing an updated portion of the temporallystored data file. The DS processing module 350 issues a random writedata response 590 to the user device 14 to acknowledge execution of therandom write data request 588. Alternatively, or in addition to, the DSprocessing module 350 may receive a read data request from the userdevice 14 to read one or more data segments of the at least some of datasegments of the plurality of data segments. The DS processing module 350issues a read data response to the user device that includes therequested one or more data segments in response to the read datarequest.

The user device 14 issues a close write file request 592 to the DSprocessing module 350 when the user device 14 determines to end therandom write process on the data file. For each data segment of the atleast some of the plurality of data segments, the DS processing module350 encodes the data segment using the dispersed storage error codingfunction to produce a set of encoded data slices, generates a set ofwrite slice requests 582 that includes the set of encoded data slicesand the common transaction number, and outputs the set of write slicerequests 582 to the DSN memory 352. When receiving a favorable number ofwrite slice responses 584 (e.g., a write threshold number of write sliceresponses indicating successful storage for each set of encoded dataslices), the DS processing module 350 issues one or more sets of committransaction requests 594 to the set of DS units 354 that includes thecommon transaction number. The DS processing module 350 receives committransaction responses 596 from the set of DS units 354 indicating astatus of a commit operation. The DS processing module 350 issues aclose write file response 598 to the user device 14 that includes statusof the commit operation based on the received commit transactionresponses 596.

FIG. 45B is a flowchart illustrating an example of storing datautilizing random writes. The method begins at step 600 where aprocessing module (e.g., of a dispersed storage (DS) processing module)establishes a plurality of temporary data segments in accordance with areceived open write file request. The establishing includes one or moreof receiving the open write file request, partitioning a data file ofthe open write file request to produce the plurality of temporary datasegments, selecting at least some of the plurality of temporary datasegments, and temporarily storing the at least some of the plurality oftemporary data segments in a local memory.

The method continues at step 602 where the processing module encodes oneor more of the plurality of temporary data segments to produce sets ofslices. The encoding includes selecting the one or more of the pluralityof temporary data segments based on a likelihood of being updatedindicator of the open write file request. For example, the processingmodule selects the one or more of the plurality of temporary datasegments as data segments that are likely not to be updated during arandom write process. The method continues at step 604 where theprocessing module initiates storage of the sets of slices in a DS unitset. The initiating includes generating at least one set of write slicerequests to include the common transaction number and the sets ofslices, outputting the at least one set of write slice requests to theDS unit set, and receiving write slice responses indicating status ofsome of the write slice requests.

The method continues at step 606 where the processing module updates adata segment of the plurality of temporary data segments to include adata portion of a received random write data request. The updatingincludes receiving the random write data request, overwriting and/orappending the data portion with regards to the data segment, and issuinga random write data response to a requesting entity to acknowledge therandom write data request. When receiving a close write file request,the method continues at step 608 where the processing module encodes anyunsynchronized data segments (e.g., data segments that have not beenstored in the DS unit set) of the plurality of temporary data segmentsto produce one or more sets of remaining slices. The encoding includesidentifying the unsynchronized data segments and encoding eachunsynchronized data segment using a dispersed storage error codingfunction to produce the corresponding set of remaining slices.

The method continues at step 610 where the processing module initiatesstorage of the one or more sets of remaining slices in the DS unit set.The initiating of the storage includes generating one or more sets ofwrite slice requests to include the one or more sets of remaining slicesand outputting the one or more sets of write slice requests to the DSunit set. The method continues at step 612 where the processing modulecompletes storage of the plurality of temporary data segments in the DSunit set. The completing of the storage includes one or more ofdetermining whether at least a write threshold number of favorable writeslice responses have been received for each data segment of theplurality of decoded data segments, generating one or more sets ofcommit transaction requests that includes the common transaction number,and outputting the one or more sets of commit transaction requests tothe DS unit set. In addition, the processing module may issue a closefile response to the requesting entity based on receiving a favorablenumber of commit transaction responses from the DS unit set. Forexample, the processing module receives at least a write thresholdnumber of favorable commit transaction responses from the DS unit setfor each data segment of the plurality of temporary data segments.

FIGS. 46A, D, and E are schematic block diagrams of an embodiment of adispersed storage network (DSN) that includes two or more distributedstorage and task (DST) client modules A-B, the network 24 of FIG. 1, anda DST execution (EX) unit set 620. The two or more DST client modulesA-B may be implemented utilizing the DST client module 34 of FIG. 1.Each DST client module A-B includes the outbound DS processing module 80of FIG. 3. The DST execution unit set 620 may include any number of DSTexecution units. For example, the DST execution unit set 620 includesDST execution units 1-5 when the DST execution unit set 620 includesfive DST execution units. Each DST execution unit 1-5 may be implementedutilizing the DST execution unit 36 of FIG. 1. Each DST execution unit1-5 includes the processing module 84 and the memory 88 of FIG. 3.

The DSN further includes at least one memory module, where the memorymodule includes a first storage device associated with the DST clientmodules A-B, a second storage device associated with the DST executionunits 1-5, and a third storage device associated with the DST clientmodules A-B. The first and third storage devices may be the same ordifferent storage devices. The first and third storage devices storeoperational instructions for execution by the DST client modules A-B.For example, the outbound DS processing module 80 of DST client module Aexecutes the stored operational instructions of the first storage deviceand the third storage device. As another example, the outbound DSprocessing module 80 of DST client module B executes the storedoperational instructions of the first storage device and the thirdstorage device. The second storage device stores operationalinstructions for execution by the DST execution units 1-5. For example,the processing module 84 of DST execution unit 1 executes the storedoperational instructions of the second storage device.

The DSN functions to store a data object in the DST execution unit set620 in accordance with a write conflict resolution approach. As aspecific example, the DST client modules A-B nearly concurrentlyinitiate first (e.g., from A) and second (e.g., from B) transactions towrite a data object Z to the DST execution unit set 620, the DST clientmodule A cancels the first transaction when determining that the DSTclient module B has write priority over the DST client module A, and theDST client module B completes the second transaction when determiningthat the DST client module B has write priority over the DST clientmodule A. As another specific example, the DST client modules A-B nearlyconcurrently initiate the first and second transactions to write thedata object Z to the DST execution unit set 620, the DST client module Bcancels the second transaction when determining that the DST clientmodule A has write priority over the DST client module B, and the DSTclient module A completes the first transaction when determining thatthe DST client module A has write priority over the DST client module B.Hereafter, the DST client module A may be referred to as a first clientdevice, the DST client module B may be referred to as a second clientdevice, and a DST execution unit may be referred to as a storage unit.

FIG. 46A illustrates the example of the DST client modules A-B nearlyconcurrently initiating first and second transactions to write the dataobject Z to the DST execution unit set 620. Hereafter, operationalexamples of the outbound DS processing module 80 of the DST clientmodules A-B and processing module 84 of the DST execution units 1-5includes execution of the operational instructions stored by the first,second, and third storage device of the memory module even though notexplicitly stated.

As a specific example of the initiating of the first and secondtransactions, the DST client modules A-B each receive a store dataobject Z request 622 at substantially the same timeframe, where thestore data object Z request 622 includes one or more of the data objectZ, and a data identifier (ID) of the data object Z. The data object Zreceived by the DST client modules A-B may be the same or differentrevisions.

The DST client modules A-B each divide the data object Z into aplurality of data segments and encode each data segment using adispersed storage error coding function to produce a set of encoded dataslices. For example, the DST client module A divides the data object Zinto 100 data segments and encodes a first data segment to produce afirst set of encoded data slices (e.g., encoded data slices Z-1-1,Z-2-1, Z-3-1, Z-4-1, and Z-5-1) and the DST client module B divides thedata object Z into the 100 data segments and encodes the first datasegment to produce a second set of encoded data slices (e.g., encodeddata slices Z-1-1, Z-2-1, Z-3-1, Z-4-1, and Z-5-1). The first and secondset of encoded data slices are substantially the same when the receivedrevisions of the data object Z are substantially the same and the firstand second set of encoded data slices are not substantially the samewhen the received revisions of the data object Z are not substantiallythe same.

Having produced the first and second sets of encoded data slices, theoutbound DS processing module 80 of the DST client module A transmits afirst set of initiate write transaction requests A regarding the firstset of encoded data slices to the DST execution unit set 620. Forexample, the DST client module A generates a first set of write slicerequests 1-A, 2-A, 3-A, 4-A, and 5-A to include the first set of encodeddata slices Z-1-1, Z-2-1, Z-3-1, Z-4-1, and Z-5-1, a set of slice names,and a first transaction number; and sends, via the network 24, the firstset of write slice requests 1-A, 2-A, 3-A, 4-A, and 5-A to the DSTexecution units 1-5.

The outbound DS processing module 80 of the DST client module Btransmits, nearly concurrently with the transmitting by the DST clientmodule A, a second set of initiate write transaction requests Bregarding the second set of encoded data slices to the DST executionunit set 620. For example, the outbound DST client module B generates asecond set of write slice requests 1-B, 2-B, 3-B, 4-B, and 5-B toinclude the second set of encoded data slices Z-1-1, Z-2-1, Z-3-1,Z-4-1, and Z-5-1, the set of slice names, and a second transactionnumber; and sends, via the network 24, the second set of write slicerequests 1-B, 2-B, 3-B, 4-B, and 5-B to the DST execution units 1-5.Examples of the transmitting by the DST client module B nearlyconcurrently with the transmitting by the DST client module A arediscussed in greater detail with reference to FIG. 46B.

Each processing module 84 of each DST execution unit 1-5 temporarilystores one of the first set of encoded data slices in the memory 88 whenthe one of the first set of write slice requests is received. Eachprocessing module 84 of each DST execution unit 1-5 temporarily storesone of the second set of encoded data slices in the memory 88 when theone of the second set of write slice requests is received (e.g.,represented as shaded slices of FIG. 46A). The processing module 84 maydelete the one of the first set of encoded data slices when a rollbacktimeframe has expired (e.g., one minute since temporarily storing thefirst set of encoded data slices) without receiving a commit transactionrequest that includes the first transaction number. The processingmodule 84 may delete the one of the second set of encoded data sliceswhen the rollback timeframe has expired (e.g., one minute sincetemporarily storing the second set of encoded data slices) withoutreceiving another commit transaction request that includes the secondtransaction number.

Having received the first and second sets of encoded data slices, theprocessing module 84 of the DST execution unit 1 determines whether theone of the first set of write slice requests was received before the oneof the second set of write requests or whether the one of the second setof write slice requests was received before the one of the first set ofwrite slice requests. As a specific example, the write slice requests1-A, 2-A, and 3-A from the DST client module A were received by DSTexecution units 1-3 before the write slice requests 1-B, 2-B, and 3-Bfrom the DST client module B and the write slice requests 4-B and 5-Bfrom the DST client module B were received by DST execution units 4-5before the write slice requests 4-A and 5-A from the DST client moduleA. Timing of such an example is discussed in greater detail withreference to FIG. 46B.

As an instance of the example, the processing module 84 indicates thatthe one of the first set of write slice requests was received before theone of the second set of write slice requests when a comparison of theslice name of the one of the first set of write slice requests to a listof locked slice names indicates that the slice name of the one of thefirst set of write slice requests is not locked yet. As anotherinstance, the processing module 84 indicates that the one of the secondset of write slice requests was received before the one of the first setof write slice requests when the comparison of the slice name of the oneof the second set of write slice requests to the list of locked slicenames indicates that the slice name of the one of the second set ofwrite slice requests is not locked yet.

When the one of the first set of write slice requests is received beforethe one of the second set of write slice requests, the processing module84 of the DST execution unit 1 generates a first write response 1message that includes one or more of an indication that the slice name(e.g., of the first data segment, of the data object) is locked for theDST client module A, the first transaction number (e.g., now associatedwith the lock), an estimated duration of the lock, and a storage unitscore value. The storage unit score value for DST execution unit 1includes a unique value of 1 associated with DST execution unit 1.

Each DST execution unit 1-5 of the DST execution unit set 620 isassociated with a unique storage unit score value of a set of uniquestorage unit score values where each storage unit score value isdifferent from every other storage unit score value. For example, theDST execution unit 1 is associated with a storage unit score value of1,the DST execution unit 2 is associated with a storage unit score valueof 2, the DST execution unit 3 is associated with a storage unit scorevalue of 4, the DST execution unit 4 is associated with a storage unitscore value of 8, and the DST execution unit 5 is associated with thestorage unit score value of 16. The score values may be the same ordifferent for any of the data object, another data object, the firstdata segment, another data segment, and a different two or more DSTclient modules.

Having generated the first write response 1 message, the processingmodule 84 of the DST execution unit 1 sends, via the network 24, thefirst write response 1 message to the DST client module A in response toreceiving the one of the first set of write requests. The processingmodule 84 of the DST execution unit 1 sends, via the network 24, thefirst write response 1 message to the DST client module B in response toreceiving the one of the second set of write requests.

When the one of the second set of write slice requests is receivedbefore the one of the first set of write slice requests, the processingmodule 84 of the DST execution unit 4 generates a second write response4 message that includes one or more of an indication that the slice name(e.g., of the first data segment, of the data object) is locked for theDST client module B, the second transaction number (e.g., now associatedwith the lock), the estimated duration of the lock, and the storage unitscore value. The storage unit score value for DST execution unit 4includes the unique value of 8 associated with DST execution unit 4. Asan example of generating the second write response 4, the second writeslice response 4 includes a slice name of Z-4-1, an assigned lockingclient ID of B as the indication that the slice name is locked for theDST client module B, and the DST execution unit 4 lock score of 8.

Having generated the second write response 4 message, the processingmodule 84 of the DST execution unit 4 sends, via the network 24, thesecond write response 4 message to the DST client module A in responseto receiving the one of the first set of write requests. The processingmodule 84 of the DST execution unit 4 sends, via the network 24, thesecond write response 4 message to the DST client module B in responseto receiving the one of the second set of write requests. The DST clientmodules A-B receive the locking information 624 that includes the writeresponse messages from each of the DST execution units 1-5. As such,each DST client module A-B receives substantially the same lockinginformation 624 and hence substantially the same storage unit scorevalues for further processing.

FIG. 46B is a diagram illustrating an example of timing of a storageprocess of the example where the DST client modules A-B nearlyconcurrently initiate first (e.g., from A) and second (e.g., from B)transactions to write the data object Z to the DST execution unit set620 of FIG. 46A. The diagram illustrates timing of messages between theDST client modules A-B and DST execution units 1-5 of the DST executionunit set 620, where time advances in a vertical direction goingdownward. The messages includes the DST client modules A-B issuing writeslice requests to the DST execution units and the DST execution unitsissuing locking information (e.g., write responses) to the DST clientmodules A-B.

The example of timing illustrates timing for an example of operationwhere write slice requests (WSR) 1-A, 2-A, and 3-A from the DST clientmodule A are received by DST execution units 1-3 before write slicerequests 1-B, 2-B, and 3-B from the DST client module B and write slicerequests 4-B and 5-B from the DST client module B are received by DSTexecution units 4-5 before the write slice requests 4-A and 5-A from theDST client module A. In the example of operation, the DST client moduleA sends the write slice request 1-A to the DST execution unit 1. The DSTexecution unit 1 issues locking information (LI) 1 to the DST clientmodule A, where the locking information 1 indicates that DST clientmodule A owns a lock associated with a first slice name of the writeslice request 1-A and a storage unit score value of 1 when the firstslice name was not locked. The DST client module B sends the write slicerequest 1-B to the DST execution unit 1. The DST execution unit 1 sendsthe locking information 1 to the DST client module B, when the firstslice name is now locked by the DST client module A. A similar scenariois depicted for messages between the DST client modules A-B and the DSTexecution unit 2.

In another aspect of the example of operation, the DST client module Asends the write slice request 3-A to the DST execution unit 3 and theDST client module B sends the write slice request 3-B to the DSTexecution unit 3. The DST execution unit 1 issues locking information(LI) 3 to the DST client modules A-B, where the locking information 3indicates that DST client module A owns a lock associated with a thirdslice name of the write slice request 3-A and a storage unit score valueof 4 when the DST execution unit 3 determines that the write slicerequest 3-A was received before the write slice request 3-B and thethird slice name was not locked.

In yet another aspect of the example of operation, the DST client moduleA sends the write slice request 4-A to the DST execution unit 4 beforethe DST client module B sends the write slice request 4-B to the DSTexecution unit 4. The DST execution unit 4 issues locking information(LI) 4 to the DST client module B, where the locking information 4indicates that DST client module B owns a lock associated with a fourthslice name of the write slice request 4 -B and a storage unit scorevalue of 8 when the DST execution unit 4 receives the write slicerequest 4-B before receiving the write slice request 4-A and the fourthslice name was not locked. The DST execution unit 4 sends the lockinginformation 4 to the DST client module A, when the fourth slice name isnow locked by the DST client module B. A similar scenario is depictedfor messages between the DST client modules A-B and the DST executionunit 5.

FIG. 46C is a table illustrating assigning storage unit score values forthe example where the DST client modules A-B nearly concurrentlyinitiate first and second transactions to write the data object Z to theDST execution unit set 620 of FIG. 46A. The table includes, for each DSTexecution unit of the DST execution units 1-5 of the DST execution unitset 620, entries for a temporary lock assignment 626, entries for anavailable score 628, entries for the assigned scores 630 each DST clientmodule A-B, and entries for total scores 632 for the DST client modulesA-B.

The table illustrates the assigning of the storage unit score values forthe example of operation where write slice requests (WSR) 1-A, 2-A, and3-A from the DST client module A are received by DST execution units 1-3before write slice requests 1-B, 2-B, and 3-B from the DST client moduleB and write slice requests 4-B and 5-B from the DST client module B arereceived by DST execution units 4-5 before the write slice requests 4-Aand 5-A from the DST client module A as discussed in the FIGS. 46A-B.The entries of the temporary lock assignment 626 indicate that the DSTclient module A has locks associated with DST execution units 1-3 andthat the DST client module B has locks associated with DST executionunits 4-5.

The entries of the available score 628 indicate assignments of storageunit score values in accordance with a storage unit score valueassignment approach. The approach includes at least one of maintainingunique values, doubling each first storage unit score value to calculatea second storage unit score value, assigning a weighted number based ona performance factor (e.g., DST execution unit performance, networkperformance), and assigning similar numbers that may require a separatetiebreaker method. As a specific example, the entries of the availablescore 628 indicates that DST execution unit 1 is associated with thestorage unit score of 1, DST execution unit 2 is associated with thestorage unit score of 2, DST execution unit 3 is associated with thestorage unit score of 4, DST execution unit 4 is associated with thestorage unit score of 8, and DST execution unit 5 is associated with thestorage unit score of 16 when the approach includes doubling eachstorage unit score value to calculate another to avoid using thetiebreaker method.

The DST client modules A-B determine the assigned scores 630 based onreceiving locking information from the DST execution units 1-5. Forexample, DST client module B receives locking information 2 from DSTexecution unit 2 indicating that the temporary lock assignment 626 isowned by DST client module A and that the available score 628 associatedwith the DST execution unit 2 is 2. As such, the DST client module Bdetermines that the DST client module A receives a score of 2.Similarly, each of the DST client modules A-B determines that the DSTclient module A receives a score of 1 from DST execution unit 1, thescore of 2 from DST execution unit 2, a score of 4 from DST executionunit 3, and that the DST client module B receives a score of 8 from DSTexecution unit 4 and a score of 16 from DST execution unit 5. Each ofthe DST client modules A-B determines entries of the total score 632 byadding up the scores. For example, the DST client modules A-B determinesthat the DST client module A receives a total score of 7 and DST clientmodule B receives a total score of 24.

Having determined the entries of the total score 632, the DST clientmodules A-B mathematically process the DST execution unit 1-5 scorevalues of the received first and second write response messages of FIG.46A to determine whether the DST client module A has the write priorityover the DST client module B, where each of the DST execution units 1-5is assigned a storage value that, when mathematically processing, avoidsa priority tie between the DST client modules A-B. For the example, theDST client modules A-B indicate that DST client module B has the writepriority over the DST client module A when the score associated with theDST client module B is greater than the score associated with DST clientmodule A when utilizing the doubling approach to avoid the tiebreaker(e.g., 24 is greater than 7).

Alternatively, when the storage unit score value assignment approachallows the total scores 632 that can result in the tie, the DST clientmodules A-B determine the write priority in accordance with a tiebreakerapproach. As a specific example, the DST client modules A-Bmathematically process the storage unit score values of the receivedfirst and second write response messages to produce the DST clientmodule A score and the DST client module B score. When the DST clientmodule A score compares favorably to the DST client module B score(e.g., the DST client module A score is greater than the DST clientmodule B score), the DST client modules A-B indicate that the DST clientmodule A has the write priority over the DST client module B. When theDST client module A score substantially equals the DST client module Bscore, the DST client modules A-B apply a tie-breaker mechanism todetermine which of the DST client modules A-B has the write priority.The tie-breaker mechanism includes one or more of randomly selecting oneof the DST client modules A-B, selecting a DST client module associatedwith a majority of the temporary lock assignments 626, selecting a DSTclient module associated with a preference indicator, and selecting theDST client module associated with a favorable performance level.

FIG. 46D illustrates the example of the DST client modules A cancelingthe first transaction when determining that the DST client module B haswrite priority over the DST client module A. As a specific example, theDST client modules A-B interpret the storage unit score values ofreceived first and second write response messages to determine whetherthe DST client module A has write priority over the DST client module B.When the DST client module A does not have the write priority over theDST client module B, the DST client module A sends a set of cancel writetransaction requests A to the DST execution unit set 620 regarding thedata object Z such that the DST execution units 1-5 cancel the first setof write slice requests 1-A through 5-A. For instance, the DST clientmodule A generates a set of rollback transaction requests A, where eachrollback transaction request A includes the first transaction number,and sends, via the network 24, the set of rollback transaction requestsA to the DST execution units 1-5.

Each of the DST execution units 1-5, in response to receiving one of theset of rollback transaction requests A, deletes the one of the first setof encoded data slices that was temporarily stored. For instance, theprocessing module 84 of the DST execution unit 1 deletes the encodeddata slice Z-1-1 that was received from DST client module A, theprocessing module 84 of the DST execution unit 2 deletes the encodeddata slice Z-2-1 that was received from DST client module A, theprocessing module 84 of the DST execution unit 3 deletes the encodeddata slice Z-3-1 that was received from DST client module A, etc.

Alternatively, when the DST client module B does not have the writepriority over the DST client module A, the DST client module sends theset of rollback requests B regarding the data object Z to the DSTexecution units 1-5 such that the DST execution units 1-5 cancel thesecond set of write slice requests. Each of the DST execution units 1-5,in response to receiving one of the set of rollback transaction requestsB, deletes the one of the second set of encoded data slices that wastemporarily stored.

FIG. 46E illustrates the example of the DST client module B completingthe second transaction when determining that the DST client module B haswrite priority over the DST client module A. As a specific example, theDST client module B receives the first and second write responsemessages from the DST execution units 1-5 and interprets the storageunit score values of received first and second write response messagesto determine whether the DST client module B has write priority over theDST client module A. When the DST client module B has the write priorityover the DST client module A, the DST client module B sends a set ofnext-phase write transaction requests B regarding the data object Z tothe DST execution unit set 620. For example, the DST client module Bgenerates a set of commit transaction requests B, where each committransaction request B includes the second transaction number, and sendsthe set of commit transaction requests B to the set of DST executionunits 1-5.

Each DST execution unit 1-5, in response to receiving one of the set ofnext-phase write requests (e.g., the commit transaction request B) fromthe DST client module B, continues with a write process of permanentlystoring the one of the second set of encoded data slices. For example,the processing module 84 of the DST execution unit 3 permanently storesencoded data slice Z-3-1 and issues a commit transaction response 3-Bindicating that the encoded data slice Z-3-1 associated with the secondtransaction number has been permanently stored. The DST client module Breceives the next-phase write transaction responses B (e.g., committransaction responses 1-B, 2-B, 3-B, 4-B, and 5-B) from the set of DSTexecution units 1-5 to confirm the permanent storage.

Alternatively, the DST client modules A-B interpret the storage unitscore values of the received first and second write response messages todetermine whether the DST client module A has the write priority overthe DST client module B. When the DST client module A has the writepriority over the DST client module B, the DST client module A sends theset of next-phase write requests regarding the data object to the DSTexecution units 1-5. In response to receiving one of the set ofnext-phase write requests, each DST execution unit 1-5 continues withthe write process of permanently storing the one of the first set ofencoded data slices (e.g., associated with the first write transactionnumber).

FIG. 46F is a flowchart illustrating an example of resolving writeconflicts. The method begins at step 640 where a first client device(e.g., of a user device that includes a distributed storage and task(DST) client module A) transmits a first set of write requests regardinga first set of encoded data slices to storage units of a dispersedstorage network (DSN), where the first client device dispersed storageerror encoded a data object to produce the first set of encoded dataslices. The method continues at step 642 where a second client device(e.g., of another user device that includes a DST client module B)transmits nearly concurrently with the transmitting by the first clientdevice, a second set of write requests regarding a second set of encodeddata slices to the storage units, where the second client devicedispersed storage error encoded the data object to produce the secondset of encoded data slices (e.g., encoded for a same portion of the dataobject as the first client device).

The method continues at step 644 where a storage unit of the storageunits receives one of the first set of write requests before one of thesecond set of write requests or receives the one of the second set ofwrite requests before the one of the first set of write requests. Themethod continues at step 646 where the storage unit temporarily storesone of the first set of encoded data slices when the one of the firstset of write requests is received and temporarily stores one of thesecond set of encoded data slices when the one of the second set ofwrite requests is received.

When the one of the first set of write requests is received before theone of the second set of write requests, the method continues at step648 where the storage unit issues a first write response message to thefirst and second client devices. As a specific example, the storage unitgenerates the first write response message that includes an indicationthat the data object is locked for the first client device and a storageunit score value. Having generated the first write response message, thestorage unit sends the first write response message to the first clientdevice in response to receiving the one of the first set of writerequests and the storage unit sends the first write response message tothe second client device in response to receiving the one of the secondset of write requests.

When the one of the second set of write requests is received before theone of the first set of write requests, the method continues at step 650where the storage unit issues a second write response message to thefirst and second client devices. As a specific example, the storage unitgenerates the second write response message that includes an indicationthat the data object is locked for the second client device and thestorage unit score value. Having generated the second write responsemessage, the storage unit sends the second write response message to thefirst client device in response to receiving the one of the first set ofwrite requests and sends the second write response message to the secondclient device in response to receiving the one of the second set ofwrite requests.

The method continues at step 652 where the first and second clientdevices receive the first and second write response messages from thestorage units. The method continues at step 654 where the first andsecond client devices interpret the storage unit score values of thereceived first and second write response messages to determine whetherthe first client device or the second client device has write priority.For example, the first and second client devices interpret the storageunit score values of the received first and second write responsemessages to determine whether the first client device has write priorityover the second client device. As another example, the first and secondclient devices interpret the storage unit score values of the receivedfirst and second write response messages to determine whether the secondclient device has write priority over the first client device.

As a specific example of the interpreting the storage unit score valuesof the received first and second write response messages to determinewhether the first client device has the write priority over the secondclient device, the first and second client devices mathematicallyprocess the storage unit score values of the received first and secondwrite response messages to determine whether the first client device hasthe write priority over the second client device, where each of thestorage units is assigned a storage value that, when mathematicallyprocessed, avoids a priority tie between the first and second clientdevices. For instance, the first and second client devices indicate thatthe first client device has the write priority over the second clientdevice when the first and second client devices process the storage unitscore values of the received first and second response messages toproduce a first client device score and a second client device score(e.g., totals including storage unit score values from all of thestorage units) where the first client device score is greater than thesecond client device score.

As another specific example of the determining whether the first clientdevice or the second client device has write priority, the first andsecond client devices interpret the storage unit score values of thereceived first and second write response messages by mathematicallyprocessing the storage unit score values of the received first andsecond write response messages to produce the first client device scoreand the second client device score. Having produced the first and secondclient device scores, the first and second client devices indicate thatthe first client device has the write priority over the second clientdevice when the first client device score compares favorably (e.g.,greater than) to the second client device score. When the first clientdevice score substantially equals the second client device score, thefirst and second client devices apply a tie-breaker mechanism todetermine which of the first and second client devices has the writepriority. The method branches to a step A of FIG. 46G when the firstclient device has the write priority. The method branches to a step B ofFIG. 46G when the second client device has the write priority.

FIG. 46G is a flowchart illustrating another example of resolving writeconflicts. The method follows, as step A from FIG. 46F, at step 656where when the second client device does not have the write priorityover the first client device, the second client device sends a set ofrollback requests regarding the data object to the storage units suchthat the storage units cancel the second set of write requests. Forexample, the second client device generates and sends a set of rollbacktransaction requests to the storage units, where the set of rollbacktransaction requests includes a second transaction number associatedwith the second set of write requests.

In response to receiving one of the set of rollback requests, the methodcontinues at step 658, where the storage unit deletes the one of thesecond set of encoded data slices that was temporally stored. When thefirst client device has the write priority over the second clientdevice, the method continues at step 660 where the first client devicesends a set of next-phase write requests regarding the data object tothe storage units. For example, the first client device generates andsends a set of commit transaction requests to the storage units, wherethe set of commit transaction requests includes a first transactionnumber associated with the first set of write requests. In response toreceiving one of the set of next-phase write requests, the methodcontinues at step 662 where the storage unit continues with a writeprocess of permanently storing the one of the first set of encoded dataslices. For example, the storage unit indicates that the one of thefirst set of encoded data slices is available for retrieval and issues acommit transaction response to the first client device indicating thatthe corresponding commit transaction request has been successfullyexecuted. Alternatively, the storage unit continues with the writeprocess of permanently storing the one of the first set of encoded dataslices in response to the receiving the one of the set of next-phasewrite requests from the first client device when receiving the one ofthe set of rollback requests (e.g., associated with a lock) from thesecond client device.

Alternatively, the method follows, as step B from FIG. 46F, at step 664where when the first client device does not have the write priority overthe second client device, the first client device sends the set ofrollback requests regarding the data object to the storage units suchthat the storage units cancel the first set of write requests. Forexample, the first client device generates and sends the set of rollbacktransaction requests to the storage units, where the set of rollbacktransaction requests includes the first transaction number associatedwith the first set of write requests.

In response to receiving one of the set of rollback requests, the methodcontinues at step 666, where the storage unit deletes the one of thefirst set of encoded data slices that was temporally stored. When thesecond client device has the write priority over the first clientdevice, the method continues at step 668 where the second client devicesends the set of next-phase write requests regarding the data object tothe storage units. For example, the second client device generates andsends the set of commit transaction requests to the storage units, wherethe set of commit transaction requests includes the second transactionnumber associated with the second set of write requests. In response toreceiving one of the set of next-phase write requests, the methodcontinues at step 670 where the storage unit continues with the writeprocess of permanently storing the one of the second set of encoded dataslices. For example, the storage unit indicates that the one of thesecond set of encoded data slices is available for retrieval and issuesthe commit transaction response to the second client device indicatingthat the corresponding commit transaction request has been successfullyexecuted. Alternatively, the storage unit continues with the writeprocess of permanently storing the one of the second set of encoded dataslices in response to the receiving the one of the set of next-phasewrite requests from the second client device when receiving the one ofthe set of rollback requests (e.g., associated with a lock) from thefirst client device.

FIG. 47A is a schematic block diagram of another embodiment of adispersed storage system that includes the dispersed storage (DS)processing module 350 of FIG. 40A, a completeness module 678, and thedispersed storage network (DSN) memory 352 of FIG. 40A. The DSN memory352 includes at least one DS unit set of a set of DS units 354 of FIG.40A. The completeness module 678 may be implemented utilizing the DSprocessing module 350.

The system functions to store a very large data object in the DSN memory352. The DS processing module 350 updates an active write process listin a hierarchical index stored in the DSN memory 352 to indicate astoring process is ongoing for the very large data object. The updatingincludes generating a list entry that includes one or more of a dataidentifier of the very large data object, a DS processing moduleidentifier, a data transaction number, and a source name associated withthe very large data object. The updating further includes issuing a setof index slice requests 680 to the DSN memory 352 to read acorresponding entry of the hierarchical index, receiving index sliceresponses 682, decoding index slices of the received index sliceresponses 682 using a dispersed storage error coding function to recovera portion of the hierarchical index, updating the portion of thehierarchical index with the list entry, encoding the updated portion ofthe hierarchical index using the dispersed storage error coding functionto produce a set of updated index slices, issuing another set of indexslice requests 680 to write the updated portion of the hierarchicalindex to the DSN memory 352, receiving at least a write threshold numberof favorable other index slice responses 682 from the DSN memory 352with regards to the other set of index slice requests 680, and issuingyet another set of index slice requests 680 to the DSN memory 352 thatincludes a set of commit transaction requests to complete storage of theupdated index slices.

The DS processing module 350 generates a set of active slice names basedon the data identifier (ID) and issues a set of data slice accessrequests 684 that includes a set of write requests including the set ofactive slice names, an active transaction number, and a set of dummyslices (e.g., null slices) to the DSN memory 352. The generatingincludes at least one of performing a lookup in a data ID to activeslice names list and performing a deterministic function on the data IDto produce the set of active slice names. For example, the DS processingmodule 350 performs a mask generating function on the data ID to producea source name that is utilized to produce the set of active slice names.

The DS processing module 350 partitions the very large data object toproduce a plurality of data segments. For each data segment of theplurality data segments, the DS processing module 350 encodes the datasegment using the dispersed storage error coding function to produce aset of encoded data slices and issues a set of data slice accessrequests 684 including write requests that includes the set of encodeddata slices and a data transaction number to the DSN memory 352. Wheneach data segment of the plurality data segments has been encoded andwritten to the DSN memory, the DS processing module generates one ormore sets of data slice access requests 684 that includes a set ofcommit transaction requests including the data transaction number. TheDS processing module 350 outputs the one or more sets of data sliceaccess requests 684 to the DSN memory 352 to make the very large dataobject visible for subsequent read operations. The DS processing module350 updates the active write process list to exclude the data ID (e.g.,retrieve the hierarchical index portion, update and/or delete the entry,store the updated hierarchical index portion in the DSN memory). The DSprocessing module 350 issues a set of data slice access requests 684 tothe DSN memory 352 that includes a set of rollback transaction requestsincluding the active transaction number.

During the active write process, the completeness module 678 is operableto access the active write process list in the hierarchical index of theDSN memory 352 to identify the data ID. As a specific example, thecompleteness module 678 generates the set of active slice names based onthe data ID and issues a set of data slice access requests 684 thatincludes a set of write requests including the set of active slicenames, a random transaction number, and null slices (e.g., to test for alock conflict). When receiving a write threshold number of favorable(e.g., no lock conflict) data slice access responses 686 thecompleteness module 678 initiates a cleanup process to delete one ormore data segments of the plurality of data segments from the DSN memory352 since the DS processing module 350 has taken too long to write thevery large data object to the DSN memory 352 and the DSN memory 352 hasautomatically timed out and rolled back the lock on the active slicenames (e.g., the DS processing module 350 may have crashed or lostcommunication with the DSN memory 352). The cleanup process includes thecompleteness module 678 issuing data slice access requests 684 (e.g.,delete requests and/or rollback transaction requests) to delete allencoded data slices associated with the source name.

FIG. 47B is a flowchart illustrating an example of writing data. Themethod begins at step 690 where a processing module (e.g., of adispersed storage (DS) processing module) updates an active writeprocess list to include an entry for a data object to be stored in adispersed storage network (DSN) memory. The updating includes one ormore of retrieving index slices from the DSN memory, decoding the indexslices to reproduce an index, updating the index, encoding the updatedindex, and storing updated index slices in the DSN memory. The methodcontinues at step 692 where the processing module obtains a write lockon a set of active slice names associated with the data object. Theobtaining includes generating the set of active slice names based on adata identifier (ID) associated with the data object (e.g., performing adeterministic function on the data ID). The method continues at step 694where the processing module partitions the data object into a pluralityof data segments in accordance with a data segmentation approach.

For each data segment of the plurality data segments, the methodcontinues at step 696 where the processing module initiates writing thedata segment to the DSN memory. The initiating includes encoding thedata segment using a dispersed storage error coding function to producea set of encoded data slices and issuing a set of write requests thatincludes the set of encoded data slices and a data transaction number.When the initiation of writing each data segment of the plurality ofdata segments has been successfully completed, the method continues atstep 698 where the processing module completes writing the plurality ofdata segments to the DSN memory. The processing module indicatessuccessful completion of writing each data segment when thecorresponding write threshold number of favorable write slice responseshas been received with regards to write slice requests of the datasegment. The completion of the writing includes issuing a set of committransaction requests that includes the data transaction number to theDSN memory.

The method continues at step 700 where the processing module updates theactive write process list to exclude the entry for the data object. Theupdating includes retrieving a portion of the index that includes theentry, deleting the entry or deleting the data ID from the entry toproduce an updated portion of the index, and storing the updated portionof the index in the DSN memory. The method continues at step 702 wherethe processing module releases the write lock on the set of active slicenames associated with the data object. The releasing includes issuing aset of rollback transaction requests to the DSN memory that includes theactive transaction number.

FIG. 47C is a flowchart illustrating an example of deleting partiallywritten data. The method begins at step 704 where a processing module(e.g., of a completeness module) identifies a data object being writtento a dispersed storage network (DSN) memory. The identifying includesaccessing an active write process list and extracting a data identifier(ID) of the data object being written to the DSN memory. The methodcontinues at step 706 where the processing module determines if a writelock on a set of active slice names associated with the data object canbe obtained. The determining includes generating the set of active slicenames based on the data ID (e.g., performing a deterministic function onthe data ID to produce a source name utilized to produce the set ofactive slice names), issuing a set of write slice requests that includesthe set of active slice names and a random transaction number, receivingwrite slice responses indicating whether the write lock was obtained fora dispersed storage (DS) unit of the DSN memory, and indicating that thewrite lock was obtained when a write threshold number of write lockshave been obtained from a write threshold number of DS units.

When a write lock on the set of active slice names associated with thedata object can be obtained, the method continues at step 708 where theprocessing module identifies one or more portions of the data objecttemporarily stored in the DSN memory for deletion. The identifyingincludes identifying a source name for the data object from the activewrite process list, generating a plurality of sets of slice names basedon the source name, issuing one or more sets of list slice requests tothe DSN memory, and receiving list slice responses indicating identitiesof encoded data slices for deletion. The method continues at step 710where the processing module deletes the one or more portions of the dataobject from the DSN memory. For example, the DS processing module issuesdeleteslice requests utilizing slice names for deletion. As anotherexample, the DS processing module issues a rollback transaction requestthat includes a data transaction number associated with the data object(e.g., retrieved from the active write process list).

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. Such an industry-accepted toleranceranges from less than one percent to fifty percent and corresponds to,but is not limited to, component values, integrated circuit processvariations, temperature variations, rise and fall times, and/or thermalnoise. Such relativity between items ranges from a difference of a fewpercent to magnitude differences. As may also be used herein, theterm(s) “operably coupled to”, “coupled to”, and/or “coupling” includesdirect coupling between items and/or indirect coupling between items viaan intervening item (e.g., an item includes, but is not limited to, acomponent, an element, a circuit, and/or a module) where, for indirectcoupling, the intervening item does not modify the information of asignal but may adjust its current level, voltage level, and/or powerlevel. As may further be used herein, inferred coupling (i.e., where oneelement is coupled to another element by inference) includes direct andindirect coupling between two items in the same manner as “coupled to”.As may even further be used herein, the term “operable to” or “operablycoupled to” indicates that an item includes one or more of powerconnections, input(s), output(s), etc., to perform, when activated, oneor more its corresponding functions and may further include inferredcoupling to one or more other items. As may still further be usedherein, the term “associated with”, includes direct and/or indirectcoupling of separate items and/or one item being embedded within anotheritem. As may be used herein, the term “compares favorably”, indicatesthat a comparison between two or more items, signals, etc., provides adesired relationship. For example, when the desired relationship is thatsignal 1 has a greater magnitude than signal 2, a favorable comparisonmay be achieved when the magnitude of signal 1 is greater than that ofsignal 2 or when the magnitude of signal 2 is less than that of signal1.

As may also be used herein, the terms “processing module”, “processingcircuit”, and/or “processing unit” may be a single processing device ora plurality of processing devices. Such a processing device may be amicroprocessor, micro-controller, digital signal processor,microcomputer, central processing unit, field programmable gate array,programmable logic device, state machine, logic circuitry, analogcircuitry, digital circuitry, and/or any device that manipulates signals(analog and/or digital) based on hard coding of the circuitry and/oroperational instructions. The processing module, module, processingcircuit, and/or processing unit may be, or further include, memoryand/or an integrated memory element, which may be a single memorydevice, a plurality of memory devices, and/or embedded circuitry ofanother processing module, module, processing circuit, and/or processingunit. Such a memory device may be a read-only memory, random accessmemory, volatile memory, non-volatile memory, static memory, dynamicmemory, flash memory, cache memory, and/or any device that storesdigital information. Note that if the processing module, module,processing circuit, and/or processing unit includes more than oneprocessing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,and/or processing unit implements one or more of its functions via astate machine, analog circuitry, digital circuitry, and/or logiccircuitry, the memory and/or memory element storing the correspondingoperational instructions may be embedded within, or external to, thecircuitry comprising the state machine, analog circuitry, digitalcircuitry, and/or logic circuitry. Still further note that, the memoryelement may store, and the processing module, module, processingcircuit, and/or processing unit executes, hard coded and/or operationalinstructions corresponding to at least some of the steps and/orfunctions illustrated in one or more of the Figures. Such a memorydevice or memory element can be included in an article of manufacture.

The present invention has been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claimed invention. Further, theboundaries of these functional building blocks have been arbitrarilydefined for convenience of description. Alternate boundaries could bedefined as long as the certain significant functions are appropriatelyperformed. Similarly, flow diagram blocks may also have been arbitrarilydefined herein to illustrate certain significant functionality. To theextent used, the flow diagram block boundaries and sequence could havebeen defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claimed invention. One of average skill in the artwill also recognize that the functional building blocks, and otherillustrative blocks, modules and components herein, can be implementedas illustrated or by discrete components, application specificintegrated circuits, processors executing appropriate software and thelike or any combination thereof.

The present invention may have also been described, at least in part, interms of one or more embodiments. An embodiment of the present inventionis used herein to illustrate the present invention, an aspect thereof, afeature thereof, a concept thereof, and/or an example thereof. Aphysical embodiment of an apparatus, an article of manufacture, amachine, and/or of a process that embodies the present invention mayinclude one or more of the aspects, features, concepts, examples, etc.described with reference to one or more of the embodiments discussedherein. Further, from figure to figure, the embodiments may incorporatethe same or similarly named functions, steps, modules, etc. that may usethe same or different reference numbers and, as such, the functions,steps, modules, etc. may be the same or similar functions, steps,modules, etc. or different ones.

While the transistors in the above described figure(s) is/are shown asfield effect transistors (FETs), as one of ordinary skill in the artwill appreciate, the transistors may be implemented using any type oftransistor structure including, but not limited to, bipolar, metal oxidesemiconductor field effect transistors (MOSFET), N-well transistors,P-well transistors, enhancement mode, depletion mode, and zero voltagethreshold (VT) transistors.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of the various embodimentsof the present invention. A module includes a processing module, afunctional block, hardware, and/or software stored on memory forperforming one or more functions as may be described herein. Note that,if the module is implemented via hardware, the hardware may operateindependently and/or in conjunction software and/or firmware. As usedherein, a module may contain one or more sub-modules, each of which maybe one or more modules.

While particular combinations of various functions and features of thepresent invention have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent invention is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. A method for execution by one or more processingmodules of one or more computing devices of a dispersed storage network(DSN), the method comprises: transmitting, by a first client device, afirst set of write requests regarding a first set of encoded data slicesto storage units of the DSN, wherein the first client device dispersedstorage error encoded a data object to produce the first set of encodeddata slices; transmitting, by a second client device and nearlyconcurrently with the transmitting by the first client device, a secondset of write requests regarding a second set of encoded data slices tothe storage units, wherein the second client device dispersed storageerror encoded the data object to produce the second set of encoded dataslices; for a storage unit of the storage units: receiving one of thefirst set of write requests before one of the second set of writerequests or receiving the one of the second set of write requests beforethe one of the first set of write requests; when the one of the firstset of write requests is received before the one of the second set ofwrite requests: generating a first write response message that includesan indication that the data object is locked for the first client deviceand a storage unit score value; sending the first write response messageto the first client device in response to receiving the one of the firstset of write requests; and sending the first write response message tothe second client device in response to receiving the one of the secondset of write requests; when the one of the second set of write requestsis received before the one of the first set of write requests:generating a second write response message that includes an indicationthat the data object is locked for the second client device and thestorage unit score value; sending the second write response message tothe first client device in response to receiving the one of the firstset of write requests; and sending the second write response message tothe second client device in response to receiving the one of the secondset of write requests; receiving, by the first client device, first andsecond write response messages from the storage units; interpreting, bythe first client device, storage unit score values of the received firstand second write response messages to determine whether the first clientdevice has write priority over the second client device; and when thefirst client device has the write priority over the second clientdevice, sending, by the first client device, a set of next-phase writerequests regarding the data object to the storage units.
 2. The methodof claim 1 further comprises: when the first client device does not havethe write priority over the second client device, sending, by the firstclient device, a set of rollback requests regarding the data object tothe storage units such that the storage units cancel the first set ofwrite requests.
 3. The method of claim 1 further comprises: receiving,by the second client device, the first and second write responsemessages from the storage units; interpreting, by the second clientdevice, the storage unit score values of the received first and secondwrite response messages to determine whether the second client devicehas the write priority over the first client device; and when the secondclient device has the write priority over the first client device,sending, by the second client device, the set of next-phase writerequests regarding the data object to the storage units.
 4. The methodof claim 3 further comprises: when the second client device does nothave the write priority over the first client device, sending, by thesecond client device, a set of rollback requests regarding the dataobject to the storage units such that the storage units cancel thesecond set of write requests.
 5. The method of claim 1, wherein theinterpreting the storage unit score values of the received first andsecond write response messages further comprises: mathematicallyprocessing the storage unit score values of the received first andsecond write response messages to determine whether the first clientdevice has the write priority over the second client device, whereineach of the storage units is assigned a storage value that, whenmathematically processing, avoids a priority tie between the first andsecond client devices.
 6. The method of claim 1, wherein theinterpreting the storage unit score values of the received first andsecond write response messages further comprises: mathematicallyprocessing the storage unit score values of the received first andsecond write response messages to produce a first client device scoreand a second client device score; when the first client device scorecompares favorably to the second client device score, indicating thatthe first client device has the write priority over the second clientdevice; and when the first client device score substantially equals thesecond client device score, applying a tie-breaker mechanism todetermine which of the first and second client devices has the writepriority.
 7. The method of claim 1 further comprises: temporarilystoring, by the storage unit, one of the first set of encoded dataslices when the one of the first set of write requests is received; andtemporarily storing, by the storage unit, one of the second set ofencoded data slices when the one of the second set of write requests isreceived.
 8. The method of claim 7 further comprises: in response toreceiving one of the set of next-phase write requests, continuing, bythe storage unit, with a write process of permanently storing the one ofthe first set of encoded data slices; and in response to receiving oneof a set of rollback requests, deleting, by the storage unit, the one ofthe second set of encoded data slices that was temporarily stored. 9.The method of claim 7 further comprises: in response to receiving one ofa second set of next-phase write requests from the second client device,continuing, by the storage unit, with a write process of permanentlystoring the one of the second set of encoded data slices; and inresponse to receiving one of a set of rollback requests from the firstclient device, deleting, by the storage unit, the one of the first setof encoded data slices that was temporarily stored.
 10. A memory moduleof a dispersed storage network (DSN), the memory module comprises: afirst storage device that stores operational instructions that, whenexecuted by a first client device or a second client device, causes thefirst client device or the second client device to: transmit, as thefirst client device, a first set of write requests regarding a first setof encoded data slices to storage units of the DSN, wherein the firstclient device dispersed storage error encoded a data object to producethe first set of encoded data slices; transmit, as the second clientdevice and nearly concurrently with the transmitting by the first clientdevice, a second set of write requests regarding a second set of encodeddata slices to the storage units, wherein the second client devicedispersed storage error encoded the data object to produce the secondset of encoded data slices; a second storage device that storesoperational instructions that, when executed by a storage unit, causesthe storage unit to: determine whether one of the first set of writerequests was received before one of the second set of write requests orwhether the one of the second set of write requests was received beforethe one of the first set of write requests; when the one of the firstset of write requests is received before the one of the second set ofwrite requests: generate a first write response message that includes anindication that the data object is locked for the first client deviceand a storage unit score value; send the first write response message tothe first client device in response to receiving the one of the firstset of write requests; and send the first write response message to thesecond client device in response to receiving the one of the second setof write requests; when the one of the second set of write requests isreceived before the one of the first set of write requests: generate asecond write response message that includes an indication that the dataobject is locked for the second client device and the storage unit scorevalue; send the second write response message to the first client devicein response to receiving the one of the first set of write requests; andsend the second write response message to the second client device inresponse to receiving the one of the second set of write requests; and athird storage device that stores operational instructions that, whenexecuted by the first client device or the second client device, causesthe first client device or the second client device to: interpretstorage unit score values of received first and second write responsemessages to determine whether the first client device has write priorityover the second client device; and when the first client device has thewrite priority over the second client device, send, as the first clientdevice, a set of next-phase write requests regarding the data object tothe storage units.
 11. The memory module of claim 10 further comprises:the third storage device further stores operational instructions that,when executed by the first client device or the second client device,further causes the first client device or the second client device to:when the first client device does not have the write priority over thesecond client device, send, as the first client device, a set ofrollback requests regarding the data object to the storage units suchthat the storage units cancel the first set of write requests.
 12. Thememory module of claim 10 further comprises: the third storage devicefurther stores operational instructions that, when executed by the firstclient device or the second client device, further causes the firstclient device or the second client device to: receive, as the secondclient device, first and second write response messages from the storageunits; interpret, as the second client device, the storage unit scorevalues of the received first and second write response messages todetermine whether the second client device has the write priority overthe first client device; and when the second client device has the writepriority over the first client device, send, as the second clientdevice, the set of next-phase write requests regarding the data objectto the storage units.
 13. The memory module of claim 12 furthercomprises: the third storage device further stores operationalinstructions that, when executed by the first client device or thesecond client device, further causes the first client device or thesecond client device to: when the second client device does not have thewrite priority over the first client device, send, as the second clientdevice, a set of rollback requests regarding the data object to thestorage units such that the storage units cancel the second set of writerequests.
 14. The memory module of claim 10, wherein the operationalinstructions that, when executed by the first client device or thesecond client device, causes the first client device or the secondclient device to interpret the storage unit score values of the receivedfirst and second write response messages by: mathematically processingthe storage unit score values of the received first and second writeresponse messages to determine whether the first client device has thewrite priority over the second client device, wherein each of thestorage units is assigned a storage value that, when mathematicallyprocessing, avoids a priority tie between the first and second clientdevices.
 15. The memory module of claim 10, wherein the operationalinstructions that, when executed by the first client device or thesecond client device, causes the first client device or the secondclient device to interpret the storage unit score values of the receivedfirst and second write response messages by: mathematically processingthe storage unit score values of the received first and second writeresponse messages to produce a first client device score and a secondclient device score; when the first client device score comparesfavorably to the second client device score, indicating that the firstclient device has the write priority over the second client device; andwhen the first client device score substantially equals the secondclient device score, applying a tie-breaker mechanism to determine whichof the first and second client devices has the write priority.
 16. Thememory module of claim 10 further comprises: the second storage devicefurther stores operational instructions that, when executed by thestorage unit, further causes the storage unit to: temporarily store, bythe storage unit, one of the first set of encoded data slices when theone of the first set of write requests is received; and temporarilystore, by the storage unit, one of the second set of encoded data sliceswhen the one of the second set of write requests is received.
 17. Thememory module of claim 16 further comprises: the second storage devicefurther stores operational instructions that, when executed by thestorage unit, further causes the storage unit to: in response toreceiving one of the set of next-phase write requests, continue, by thestorage unit, with a write process of permanently storing the one of thefirst set of encoded data slices; and in response to receiving one of aset of rollback requests, delete, by the storage unit, the one of thesecond set of encoded data slices that was temporarily stored.
 18. Thememory module of claim 16 further comprises: the second storage devicefurther stores operational instructions that, when executed by thestorage unit, further causes the storage unit to: in response toreceiving one of a second set of next-phase write requests from thesecond client device, continue, by the storage unit, with a writeprocess of permanently storing the one of the second set of encoded dataslices; and in response to receiving one of a set of rollback requestsfrom the first client device, delete, by the storage unit, the one ofthe first set of encoded data slices that was temporarily stored.